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Science Book Review: Confirmatory Factor Analysis for Applied Research (Methodology in the Social...
 
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http://www.ScienceBookMix.com This is the summary of Confirmatory Factor Analysis for Applied Research (Methodology in the Social Sciences) by Timothy A. Brown PsyD.
Views: 161 ScienceBookMix
1.3 Exploratory, Descriptive and Explanatory Nature Of Research
 
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If you are having troubles with your research paper, I might have a solution for you. My full course "Research Methods for Business Students" is available on Udemy. Here you can also submit YOUR questions to me and receive FEEDBACK ON YOUR PAPER! As you are my students, the course is only for 9.99 USD with following link: https://www.udemy.com/research-methods-for-business-students/?couponCode=RESEARCH_METHODS_1
Views: 102009 MeanThat
Introduction to Confirmatory Factor Analysis in Mplus
 
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On October 10, 2018, Falynn Thompson presented this 32-minute talk at the University of Kentucky on "Introduction to Confirmatory Factor Analysis (CFA)" the first presentation in the Fall 2018 Applied Quantitative and Psychometric Series (AQPS). This presentationfocused on what is CFA, why and when to use it, how to specify the model, and interpret results from this model using Mplus Visit http://education.uky.edu/edp/apslab/e... to download the PowerPoint Handout and Mplus Data Files for this talk.
Views: 461 Michael Toland
Advance Inferential Statistical Analysis using IBM SPSS & Amos - Part VIII
 
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This lecture is from One Day Workshop “Advance Inferential Statistical Analysis using IBM SPSS 24 & AMOS 24 - Multiple Regression Analysis, Moderation Analysis, Path Analysis, Structural Equation Model (SEM), Model Fit Indices, Bootstrapping” conducted on Saturday 14th January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the second workshop of this series. This workshop is available on YouTube in eight parts. You are, currently, viewing part eight. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/1857850791118835/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIevfJ-JXk7Ox-nxw For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Een Laastse Liedje by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Bryman, A., & Bell, E. (2015). Business Research Methods. Oxford University Press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 186 Adil Bilal
Introduction to Bifactor Analysis in Mplus
 
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On November 1, 2016, Dr. Joseph Hammer and Dr. Michael Toland presented this 50-minute talk at the University of Kentucky on Bifactor Analysis in Mplus, the second presentation in the Fall 2016 Applied Quantitative and Psychometric Series (AQPS). This presentation introduced the bifactor confirmatory factor analysis (CFA) model: what it is, when to use it, how to run it in Mplus, and how to use follow-up Explained Common Variance and Omega coefficients to answer questions about the internal structure and reliability of multidimensional scales/instruments used in research. Visit https://education.uky.edu/edp/apslab/events/#Bifactor to download the PowerPoint Handout and Mplus Files for this talk.
Views: 4251 Michael Toland
EFA & CFA using IBM SPSS & Amos - Part IV
 
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This lecture is from One Day Workshop “EFA & CFA using IBM SPSS 24 & AMOS 24 - Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA)” conducted on Saturday 21st January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the third workshop of this series. This workshop is available on YouTube in six parts. You are, currently, viewing part four. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/348679915524931/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIscZQN-GrBsUAUPQ For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Kolomeika by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research. Guilford Publications. Bryman, A., & Bell, E. (2015). Business research methods. Oxford university press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39–50. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6). Pearson Prentice Hall Upper Saddle River, NJ. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 1197 Adil Bilal
SEM Episode 3: Factor Analysis
 
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In this episode of Office Hours, Patrick continues his exploration of the structural equation model by introducing latent variables. ... He begins with a conceptual definition of a latent factor and describes how latent variables can be used to capture different kinds of effects in applied research settings. He then briefly explores the exploratory factor analysis (EFA) model and uses this framework to transition to the confirmatory factor analysis (CFA) model. He describes how CFA models can be specified, how the scale of the latent factor is established, and how the model can be evaluated and potentially respecified. He concludes with a review of the unique strengths of CFA how latent factors can be used in a fully latent structural equation model (SEM) that is the topic of the following episode in this series. Bollen, K. A. (2002). Latent variables in psychology and the social sciences. Annual Review of Psychology, 53, 605-634. Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. American Psychological Association.
Sensitivity, Specificity, Screening Tests & Confirmatory Tests
 
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http://www.stomponstep1.com/sensitivity-specificity-screening-tests/ Sensitivity (Sen) & Specificity (Spec) are used to evaluate the validity of laboratory tests (not results of the tests). Basically, you use sensitivity and specificity to determine whether or not to use a certain test or to determine what situations a certain test would work best in. It is important to note that Sen and Spec are fixed for a certain test as long as you don't change the cutoff point. Therefore, Sensitivity & Specificity are not affected by changing prevalence. Both are given as a percentage ranging from 0% to 100%. Sensitivity is the percentage of patients with the disease that receive a positive result or the percentage chance that the test will correctly identify a person who actually has the disease Sensitivity = TP _ (TP + FN) or Sensitivity = TP _ Diseased Specificity is the Percentage of patients without the disease that receive a negative result Specificity = TN _ (TN+FP) or Specificity = TN _ Not Diseased Imagine you have 2 very different guns. The first gun fires when you barely touch the trigger. A strong gust of wind could set it off. The first gun has high sensitivity and low specificity. It is sensitive to the smallest of signals to fire while not being very specific to an intentional pull of the trigger. You never miss a possible chance to shoot your gun (~ Low FN), but you often accidentally fire when you shouldn't (~ High FP). The second gun only fires if you pull the trigger really hard. This gun has high specificity and low sensitivity. It is very specific to firing only when you intentionally pull the trigger (~Low FP), but it isn't very sensitive to a weak pull of the trigger (~High FN). In the real world you never have a test that is 100% Sen and 100% Spec. We are usually faced with a decision to use a test with high Sen (and lower spec) or high Spec (and lower Sen). Usually a test with high sensitivity is used as the Initial Screening Test. Those that receive a positive result on the first test will be given a second test with high specificity that is used as the Confirmatory Test. In these situations you need both tests to be positive to get a definitive diagnosis. Getting a single positive reading is not enough for a diagnosis as the individual tests have either a high chance of FP or a high chance of FN. For example, HIV is diagnosed using 2 tests. First an ELISA screening test is used and then a confirmatory Western Blot is used if the first test is positive. There are also specific situations where having a high specificity or sensitivity is really important. Consider that you are trying to screen donations to a blood bank for blood borne pathogens. In this situation you want a super high sensitivity, because the drawbacks of a false negative (spreading disease to a recipient) are way higher than the drawbacks of a false positive (throwing away 1 blood donation). Now consider you are testing a patient for the presence of a disease. This particular disease is treatable, but the treatment has very serious side effects. In this case you want a test that has high specificity, because there are major drawbacks to a false positive. Now that you have finished this video you should check out the next video in the Biostats & Epidemiology section which covers the calculation of Predictive Value Positive & Negative (http://www.stomponstep1.com/negative-positive-predictive-value-equation-calculation/). That video has some mnemonics and concepts that also apply to this video.
Views: 40263 Stomp On Step 1
Confirmatory & Exploratory Factor Analysis (SEM Tutorial Part 14) | www.pietutors.com
 
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In this video we will look at the difference between confirmatory factor analysis and exploratory factor analysis.
Views: 4512 PIE TUTORS
Research Methodology (Part 2 of 3): 14 Types of Research Methods - Where to Apply?
 
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Dr. Manishika Jain in this lecture explains the 14 major types of research methods: Basic versus Applied Research Fixed versus Flexible Research Quantitative versus Qualitative Research Experimental versus Non-Experimental Research Causal or Explanatory Research Confirmatory versus exploratory Research Descriptive Research Historical Research Diagnostic Research Prognostic Research Evaluation Research Action Research Ex-post Facto or Casual Comparative Research Correlational Research For IAS Psychology postal Course refer - http://www.examrace.com/IAS/IAS-FlexiPrep-Program/Postal-Courses/Examrace-IAS-Psychology-Series.htm Research Methodology playlist - https://www.youtube.com/playlist?list=PLW9kB_HKs3_N4-55qIi36fwdW2UaySm9Y Framework @0:12 Basic versus Applied @3:24 Fixed versus Flexible @5:19 Quantitative vs. Qualitative @6:04 Experimental vs. Non – Experimental @8:08 Exploratory vs. Confirmatory Research @10:09 Explanatory or Casual Research @12:11 Descriptive Research @13:51 Historical Research @16:24 Ex-post Factor or Casual – Comparative Research @17:56 Correlational Research @19:59 Evaluation Research @21:11 Formative vs. Summative Evaluation @22:39 Diagnostic Research @24:58 Prognostic Research @25:32 Action Research @26:11 Types of Research Problems Addressed @28:03 Research Design @30:09 Research Methodology @30:22 #Longitudinal #Posteriori #Experimental #Questionnaire #Quantitative #Descriptive #Manipulate #Fundamental #Flexible #Methodological #Manishika #Examrace different types of research methods pdf types of research ppt types of research pdf types of research methods qualitative and quantitative what are the 3 types of research types of research methods in psychology classification of research types of research based on purpose
Views: 275616 Examrace
Multigroup Confirmatory Factor Analysis in R - Class Assignment 1
 
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Recorded: Summer 2015 Lecturer: Dr. Erin M. Buchanan Packages needed: lavaan, semPlot Class assignment for structural equation modeling. Topic covers how program a multigroup confirmatory factor analysis (MGCFA) using the steps described in Brown (2006) CFA for Applied Research book. Lecture materials and assignment available at statstools.com (coming soon). Used in the following courses: Structural Equation Modeling
Views: 1358 Statistics of DOOM
EFA & CFA using IBM SPSS & Amos - Part I
 
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This lecture is from One Day Workshop “EFA & CFA using IBM SPSS 24 & AMOS 24 - Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA)” conducted on Saturday 21st January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the third workshop of this series. This workshop is available on YouTube in six parts. You are, currently, viewing part one. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/348679915524931/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIscZQN-GrBsUAUPQ For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Kolomeika by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research. Guilford Publications. Bryman, A., & Bell, E. (2015). Business research methods. Oxford university press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39–50. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6). Pearson Prentice Hall Upper Saddle River, NJ. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 2437 Adil Bilal
Applied Research
 
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Views: 83 SEAGroupLtd
EFA & CFA using IBM SPSS & Amos - Part VI
 
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This lecture is from One Day Workshop “EFA & CFA using IBM SPSS 24 & AMOS 24 - Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA)” conducted on Saturday 21st January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the third workshop of this series. This workshop is available on YouTube in six parts. You are, currently, viewing part six. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/348679915524931/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIscZQN-GrBsUAUPQ For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Kolomeika by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research. Guilford Publications. Bryman, A., & Bell, E. (2015). Business research methods. Oxford university press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39–50. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6). Pearson Prentice Hall Upper Saddle River, NJ. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 883 Adil Bilal
Exploratory Research
 
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Views: 6345 Adrian Cordero
EFA & CFA using IBM SPSS & Amos - Part V
 
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This lecture is from One Day Workshop “EFA & CFA using IBM SPSS 24 & AMOS 24 - Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA)” conducted on Saturday 21st January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the third workshop of this series. This workshop is available on YouTube in six parts. You are, currently, viewing part five. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/348679915524931/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIscZQN-GrBsUAUPQ For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Kolomeika by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research. Guilford Publications. Bryman, A., & Bell, E. (2015). Business research methods. Oxford university press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39–50. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6). Pearson Prentice Hall Upper Saddle River, NJ. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 547 Adil Bilal
Multigroup Confirmatory Factor Analysis in R - Class Assignment 2
 
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Recorded: Summer 2015 Lecturer: Dr. Erin M. Buchanan Packages needed: lavaan, semPlot Class assignment for structural equation modeling. Topic covers how program a multigroup confirmatory factor analysis (MGCFA) using the steps described in Brown (2006) CFA for Applied Research book. Additionally, this video covers the calculation of weighted average scores for latent variables, how to analyze those with a t-test, and calculation of d effect size for that difference (generally called a latent means analysis). Lecture materials and assignment available at statstools.com (coming soon). Used in the following courses: Structural Equation Modeling
Views: 1568 Statistics of DOOM
Advance Inferential Statistical Analysis using IBM SPSS & Amos - Part V
 
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This lecture is from One Day Workshop “Advance Inferential Statistical Analysis using IBM SPSS 24 & AMOS 24 - Multiple Regression Analysis, Moderation Analysis, Path Analysis, Structural Equation Model (SEM), Model Fit Indices, Bootstrapping” conducted on Saturday 14th January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the second workshop of this series. This workshop is available on YouTube in eight parts. You are, currently, viewing part five. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/1857850791118835/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIevfJ-JXk7Ox-nxw For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Een Laastse Liedje by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Bryman, A., & Bell, E. (2015). Business Research Methods. Oxford University Press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 83 Adil Bilal
EFA & CFA using IBM SPSS & Amos - Part III
 
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This lecture is from One Day Workshop “EFA & CFA using IBM SPSS 24 & AMOS 24 - Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA)” conducted on Saturday 21st January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the third workshop of this series. This workshop is available on YouTube in six parts. You are, currently, viewing part three. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/348679915524931/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIscZQN-GrBsUAUPQ For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Kolomeika by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research. Guilford Publications. Bryman, A., & Bell, E. (2015). Business research methods. Oxford university press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39–50. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6). Pearson Prentice Hall Upper Saddle River, NJ. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 732 Adil Bilal
EFA & CFA using IBM SPSS & Amos - Part II
 
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This lecture is from One Day Workshop “EFA & CFA using IBM SPSS 24 & AMOS 24 - Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA)” conducted on Saturday 21st January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the third workshop of this series. This workshop is available on YouTube in six parts. You are, currently, viewing part two. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/348679915524931/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIscZQN-GrBsUAUPQ For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Kolomeika by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research. Guilford Publications. Bryman, A., & Bell, E. (2015). Business research methods. Oxford university press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39–50. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6). Pearson Prentice Hall Upper Saddle River, NJ. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 667 Adil Bilal
Merits, Limitations & Applications of Factor Analysis (PSY)
 
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Subject : Psychology Paper : Applied Psychometrics
Views: 415 Vidya-mitra
R - Multigroup Confirmatory Factor Analysis Lecture
 
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Lecturer: Dr. Erin M. Buchanan Missouri State University Summer 2016 This video lecture covers the steps and procedures for a multigroup confirmatory factory analysis. The Brown (2006) Applied CFA terminology and procedure are used. Partial invariance procedures and latent means are discussed. Lecture materials and assignment available at statstools.com. http://statstools.com/learn/structural-equation-modeling/ Used in the following courses: Structural Equation Modeling
Views: 835 Statistics of DOOM
Mod-01 Lec-33 Factor Analysis
 
01:03:05
Applied Multivariate Statistical Modeling by Dr J Maiti,Department of Management, IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
Views: 36889 nptelhrd
Bias & Validity Definition in Research Study Design
 
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http://www.stomponstep1.com/bias-validity-definition-in-research-study-design/ Validity is how well the test or study answers the question it was supposed to answer. With regard to laboratory test results you would use sensitivity and specificity to measure validity. However, the term validity is more commonly used when referring to research. It is basically how valid the conclusions of the study are based on the study's design and results. There is internal validity which measures how well your results represent what is going on in the sample being studied and external validity which measures how well your results can be applied to other situations (or the overall population). Bias is a non-random (directional) deviation from the truth. High bias in a study means low validity and vice versa. With regards to research studies bias is problems with the study design or execution that cause you to consistency get distorted results. These results are non-random as you are consistently having the results skewed in the same direction. In most cases this means you are showing a stronger association between the factor being studied and the health outcome. Bias is different than the random error you might see with a low sample size. Bias means there is something fundamentally wrong with the study that is causing you to get incorrect results that are consistently different than the truth. You can't correct bias by having a larger sample size. The Ideal Research Study has the following characteristics: • The study population is similar to the overall population of interest • The two or more groups in the study should be as close to identical as possible at the start of the study except for the one variable you are trying to isolate • The different groups should remain close to identical throughout the study. This involves keeping as many patients as possible enrolled in the study until the end and treating the different groups the same except for the variable you are trying to isolate • All patients are compliant with any treatments or lifestyle changes assigned to them Now that you have finished this video you should check out the next video in the Biostats & Epi sections which covers Confounding, Randomization, Selection Bias & Sampling Bias (http://www.stomponstep1.com/confounding-placebo-stratification-randomization-blinding/).
Views: 29400 Stomp On Step 1
Steps in Research Proposal - Key Characteristics and Order
 
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Dr. Manishika Jain explains Steps in Research Proposal - Key Characteristics and Order Exploratory Factor Analysis @0:19 Confirmatory Factor Analysis @1:08 Traditional Approach @1:53 Structural Equation Modelling @1:30 #Scrutiny #Occupation #Component #Implemented #Predefined #Variable #Structure #Analysis #Confirmatory #Exploratory #Manishika #Examrace To register for online Paper 1 Course - https://www.doorsteptutor.com/Exams/UGC/Paper-1/Online-Crash-Course/ Dr. Manishika Jain solved the various doubts being provided by the students for the NET Paper 1 questions during the online crash course. For postal course refer - https://www.examrace.com/CBSE-UGC-NET/CBSE-UGC-NET-FlexiPrep-Program/Postal-Courses/ For Paper 1 preparation (online course, mock tests and practice questions) visit - https://www.doorsteptutor.com/Exams/UGC/Paper-1/ For optional papers - https://www.doorsteptutor.com/Exams/UGC/ Steps in Research Proposal • Identification of research topic: sources and need - theoretical and conceptual framework • Review of related Literature – studies in area of interest, local studies • Rationale and need for the study – why is this study conducted? • Definition of Terms – can be constitutive or operational. Constitutive definition elucidates a term and perhaps gives some more insight into the phenomena described by the terms & is based on theory. Operational definition provides meaning to a concept by specifying the operations that must be performed in order to measure the concept • Variables – DV, IV
Views: 4308 Examrace
Mod-01 Lec-35 Factor Analysis -- Model Adequacy, rotation, factor scores & case study
 
01:01:21
Applied Multivariate Statistical Modeling by Dr J Maiti,Department of Management, IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
Views: 7926 nptelhrd
SPSS for questionnaire analysis:  Correlation analysis
 
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Basic introduction to correlation - how to interpret correlation coefficient, and how to chose the right type of correlation measure for your situation. 0:00 Introduction to bivariate correlation 2:20 Why does SPSS provide more than one measure for correlation? 3:26 Example 1: Pearson correlation 7:54 Example 2: Spearman (rhp), Kendall's tau-b 15:26 Example 3: correlation matrix I could make this video real quick and just show you Pearson's correlation coefficient, which is commonly taught in a introductory stats course. However, the Pearson's correlation IS NOT always applicable as it depends on whether your data satisfies certain conditions. So to do correlation analysis, it's better I bring together all the types of measures of correlation given in SPSS in one presentation. Watch correlation and regression: https://youtu.be/tDxeR6JT6nM ------------------------- Correlation of 2 rodinal variables, non monotonic This question has been asked a few times, so I will make a video on it. But to answer your question, monotonic means in one direction. I suggest you plot the 2 variables and you'll see whether or not there is a monotonic relationship there. If there is a little non-monotonic relationship then Spearman is still fine. Remember we are measuring the TENDENCY for the 2 variables to move up-up/down-down/up-down together. If you have strong non-monotonic shape in the plot ie. a curve then you could abandon correlation and do a chi-square test of association - this is the "correlation" for qualitative variables. And since your 2 variables are ordinal, they are qualitative. Good luck
Views: 506769 Phil Chan
R - SEM - Multigroup CFA Class Assignment 2
 
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Lecturer: Dr. Erin M. Buchanan Missouri State University Summer 2016 This assignment video is updated from last summer with new semTools measurement invariance and partial invariance functions. Packages needed: lavaan, semPlot, semTools Class assignment for structural equation modeling. Topic covers how program a multigroup confirmatory factor analysis (MGCFA) using the steps described in Brown (2006) CFA for Applied Research book. Additionally, this video covers the calculation of weighted average scores for latent variables, how to analyze those with a t-test, and calculation of d effect size for that difference (generally called a latent means analysis). Lecture materials and assignment available at statstools.com. http://statstools.com/learn/structural-equation-modeling/ Used in the following courses: Structural Equation Modeling
Views: 1068 Statistics of DOOM
Advance Inferential Statistical Analysis using IBM SPSS & Amos - Part III
 
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This lecture is from One Day Workshop “Advance Inferential Statistical Analysis using IBM SPSS 24 & AMOS 24 - Multiple Regression Analysis, Moderation Analysis, Path Analysis, Structural Equation Model (SEM), Model Fit Indices, Bootstrapping” conducted on Saturday 14th January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the second workshop of this series. This workshop is available on YouTube in eight parts. You are, currently, viewing part three. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/1857850791118835/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIevfJ-JXk7Ox-nxw For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Een Laastse Liedje by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Bryman, A., & Bell, E. (2015). Business Research Methods. Oxford University Press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 202 Adil Bilal
R - Multigroup CFA Example
 
01:00:59
Lecturer: Dr. Erin M. Buchanan Missouri State University Summer 2016 This example covers how to perform a multigroup confirmatory factor analysis with two groups walking through the invariance steps suggested by Brown in his Applied CFA book. The lavaan and semTools packages are used to demonstrate measurement invariance and partial invariance. Lecture materials and assignment available at statstools.com. http://statstools.com/learn/structural-equation-modeling/ Used in the following courses: Structural Equation Modeling
Views: 2915 Statistics of DOOM
Applied Research Industry Breakfast
 
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Humber recently hosted a networking event to introduce industry to the college's new Centre of Technology Innovation.
Views: 498 Humber College
Advance Inferential Statistical Analysis using IBM SPSS & Amos - Part II
 
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This lecture is from One Day Workshop “Advance Inferential Statistical Analysis using IBM SPSS 24 & AMOS 24 - Multiple Regression Analysis, Moderation Analysis, Path Analysis, Structural Equation Model (SEM), Model Fit Indices, Bootstrapping” conducted on Saturday 14th January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the second workshop of this series. This workshop is available on YouTube in eight parts. You are, currently, viewing part two. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/1857850791118835/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIevfJ-JXk7Ox-nxw For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Een Laastse Liedje by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Bryman, A., & Bell, E. (2015). Business Research Methods. Oxford University Press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 176 Adil Bilal
Water Microbiology 1 | water testing and water analysis
 
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Water Microbiology 1 | water testing and water analysis - this water microbiology lecture explains about water testing to identify bacterial contamination. Web- http://www.shomusbiology.com Get the video materials (powerpoint/ script) here- http://www.shomusbiology.com/bio-materials
Views: 36886 Shomu's Biology
Advance Inferential Statistical Analysis using IBM SPSS & Amos - Part VII
 
20:55
This lecture is from One Day Workshop “Advance Inferential Statistical Analysis using IBM SPSS 24 & AMOS 24 - Multiple Regression Analysis, Moderation Analysis, Path Analysis, Structural Equation Model (SEM), Model Fit Indices, Bootstrapping” conducted on Saturday 14th January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the second workshop of this series. This workshop is available on YouTube in eight parts. You are, currently, viewing part seven. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/1857850791118835/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gYIevfJ-JXk7Ox-nxw For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Een Laastse Liedje by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Bryman, A., & Bell, E. (2015). Business Research Methods. Oxford University Press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Kenny, D. A. (2011). Measuring model fit. Retrieved November, 29, 2011. Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 286 Adil Bilal
BrisScience (September): A Stroke of Inspiration: Advancements in Stroke Research
 
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In Australia nearly 50,000 people suffer a stroke each year and there are over 470,000 stroke survivors living in Australia, a third of whom are under the age of 65. At the age of just 31, Dr Lavinia Codd became one of those statistics. The former chartered accountant is now a postdoctoral research fellow at the Queensland Brain Institute at UQ. Lavinia is investigating ways of improving cognitive recovery following stroke by activating precursor cells to increase the production of new brain cells (neurogenesis), which is a form of neuroplasticity. Her aim is to translate laboratory findings into new behavioural and pharmacological approaches to restore cognitive functions in human stroke survivors.
The Conversational Rollercoaster: ethnomethodology & conversation analysis at New Scientist Live
 
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The Conversational Rollercoaster is a new public ‘demo’ format for ethnomethodology and conversation analysis. We developed the format for New Scientist Live in collaboration with Loughborough and the CARM group in order to make it easier to explain EM/CA research in a public exhibition context. The idea is that you can take a live conversation – in this case provided by The People Speak‘s pop-up talk-show Talkaoke (http://talkaoke.com), and subject it to instant EM/CA analysis. What’s more, you can involve the public as analysts in a variety of activities – ‘being the data’ on the Talkaoke table, spotting interactional phenomena, gathering data, transcribing, analyzing and reporting findings on the ‘results wall’. You can read a nice write-up of the project on Rolsi.net here: https://rolsi.net/2016/10/10/guest-blog-saul-albert-and-colleagues-on-the-conversational-rollercoaster-emca-exhibition/
Views: 1147 Saul Albert
Time is on our side: the power of longitudinal data | George Ploubidis | TEDxLondonBusinessSchool
 
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With a focus on the development of reliable population health metrics and the evaluation of existing measurement instruments, George talks about the power of longitudinal data in understanding how life changes across generations. A population health scientist by trade and Chief Statistician of the Centre for Longitudinal Studies at the University College London, George Ploubidis’ research has centred on uncovering the socio-economic, demographic and structural determinants of population health and the mechanisms that link these over the life-course. He is particularly interested in the joint progress of health and mortality and the use of population surveys to capture macro level trends. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Views: 1401 TEDx Talks
Tutorial: Factor analysis revisited – An overview with the help of SPSS, SAS and R packages
 
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Numerous research articles and books published on Factor Analysis as it is widely applied in many of the disciplines such as Psychology & behaviour sciences and marketing where more number of observed variables is used. Factor analysis is used to reduce the number of variables which are correlated among themselves by defining them into few factors which are linear combinations of the original variables and it also the studies the underlying structure in the data set. Factor analysis [1, 2] is introduced by Spearman a century ago[3, 2,]. This paper provides an overview of Factor Analysis and how to conduct a Factor Analysis using SAS, SPSS and R statistical packages through a hypothetical data set.
Views: 6 editor ijsmi
/r/IntroPsych Research Methods
 
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Research Methods in psychology for the uReddit Intro to Psychology course.
Views: 11569 Patrick O'Connor
Exploratory research vs descriptive Research
 
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It explains the difference between exploratory research and descriptive Research
Views: 4154 Educate Motivate
Applying Basic Quantitative Research Techniques using IBM SPSS - Part II
 
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This lecture is from One Day Workshop “Applying Basic Quantitative Research Techniques using IBM SPSS – Parametric Tests, Non-Parametric Tests & Regression Analysis” conducted on Saturday 7th January, 2017 by Adil Bilal, organized by Leadership & Management Development Associates (LMDA), at Lahore School of Management, Lahore. This workshop was part of the “Research Excellence Series” training workshops. It was the first workshop of this series. This workshop is available on YouTube in seven parts. You are, currently, viewing part two. Thanks Sir Muhammad Shakaib, Sir Rizwan Danish, Sir Zahoor Sarwar, Sir Ali Sajid, Madam Alia Ahmed, Sir John Lenarcic, Sir James Gaskin and Sir Siddhi Pittayachawan, for your kind support and valuable resources, without you people, it was not possible to start this new journey. Event page: https://www.facebook.com/events/759990230822206/ Workshop Resources: https://1drv.ms/f/s!Ag5Ww3ifI4n_gP5LrnJ1vUz4YaKttw For in detail trainer Info: https://pk.linkedin.com/in/adilbilal007 https://www.facebook.com/dradilbilal https://www.researchgate.net/profile/Adil_Bilal2 Music: Planta Baja by Tres Tristes Tangos is licensed under an Attribution-Share Alike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos References Bickel, R. (2007). Multilevel Analysis for Applied Research: It’s Just Regression! Guilford Press. Bryman, A., & Bell, E. (2015). Business Research Methods. Oxford University Press. Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. SAGE. Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley & Sons.
Views: 306 Adil Bilal
Latent Class Analysis by Tarani Chandola
 
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The basic idea underlying Latent Class Analysis (LCA) is that there are unobserved subgroups of cases in the data. These unobserved subgroups form the categories of a categorical latent variable. In a statistical model of data with such unobserved subgroups, some of the parameters of the model will differ across these subgroups (the categorical latent variable). LCA is a subset of structural equation models and shares similarities with factor analysis. For more methods resources see: http://www.methods.manchester.ac.uk
Views: 5382 methodsMcr
Introduction to Mplus
 
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On October 4, 2016, David Dueber presented this 36-minute talk at the University of Kentucky on an Introduction to Mplus, the first presentation in the Fall 2016 Applied Quantitative and Psychometric Series (AQPS). This presentation focused on how to get your data ready for use in Mplus, conduct basic descriptive analyses, and the commands available in Mplus for estimating basic correlations and regression models. Visit https://education.uky.edu/edp/apslab/events/#IntroMplus to download the PowerPoint Handout and Mplus files for this talk.
Views: 5097 Michael Toland