Search results “Use of factor analysis in research”

This video provides an introduction to factor analysis, and explains why this technique is often used in the social sciences. Check out https://ben-lambert.com/econometrics-course-problem-sets-and-data/ for course materials, and information regarding updates on each of the courses. Quite excitingly (for me at least), I am about to publish a whole series of new videos on Bayesian statistics on youtube. See here for information: https://ben-lambert.com/bayesian/ Accompanying this series, there will be a book: https://www.amazon.co.uk/gp/product/1473916364/ref=pe_3140701_247401851_em_1p_0_ti

Views: 157061
Ben Lambert

Views: 16741
Marketing research and analysis

In intelligence research, personality research and other research fields of psychology, factor analytic models are used to structurize the variables' jungle.
For example: To simplify the variable structure of a personality questionnaire several questions (items), that are supposed to measure the same construct are grouped to one (latent) factor (e.g. extraversion).
But does this group of items really measure extraversion? Maybe some of the items "load" on a different factor. And Maybe other aspects of the model have flaws as well...
How well a factor model fits the data can be examined by a confirmatory factor analysis.
Keywords:
Confirmatory Factor Analysis - Factor Analysis - Psychology - Statistics - Research Methods - Personality Psychology - Extraversion - Conscientiousness - Openness - Neuroticism - Agreeableness - Five Factor Model - Big Five - Intelligence - Carroll

Views: 21478
www.LearningPsychology.net

Determining the efficiency of a number of variables in their ability to measure a single construct.
Link to Monte Carlo calculator: http://www.allenandunwin.com/spss4/further_resources.html Download the file titled MonteCarloPA.zip.

Views: 270908
TheRMUoHP Biostatistics Resource Channel

In this video lecture I explain what an exporatory factor analysis does, and how it works, and why we do it.

Views: 64508
James Gaskin

This Lecture talks about Research using software : Factor Analysis

Views: 12755
Cec Ugc

In this video we will learn the basic theoretical aspects of Factor analysis. The purpose of this video is to acquaint you to the basic terms of Factor Analysis. This will help you in various exams as well. Hope you find it useful.

Views: 4422
Rajesh Dorbala

This video demonstrates how interpret the SPSS output for a factor analysis. Results including communalities, KMO and Bartlett’s Test, total variance explained, and the rotated component matrix are interpreted.

Views: 107846
Dr. Todd Grande

In this video, we look at how to run an exploratory factor analysis (principal components analysis) in SPSS (Part 1 of 6).
Youtube SPSS factor analysis
Principal Component Analysis
YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Subscribe today!
Lifetime access to SPSS videos: http://tinyurl.com/m2532td
Video Transcript: In this video we'll take a look at how to run a factor analysis or more specifically we'll be running a principal components analysis in SPSS. And as we begin here it's important to note, because it can get confusing in the field, that factor analysis is an umbrella term where the whole subject area is known as factor analysis but within that subject there's two types of main analyses that are run. The first type is called principal components analysis and that's what we'll be running in SPSS today. And the other type is known as common factor analysis and you'll see that come up sometimes. But in my experience principal components analysis is the most commonly used procedure and it's also the default procedure in SPSS. And if you look on the screen here you can see there's five variables: SWLS 1, 2 3, 4 and 5. And what these variables are they come from the items of the Satisfaction with Life Scale published by Diener et al. And what people do is they take these five items they respond to the five items where SLWS1 is "In most ways my life is close to my ideal;" and then we have "The conditions of my life are excellent;" "I am satisfied with my life;" "So far I've gotten the important things I want in life;" and then SWLS5 is "If I could live my life over I would change almost nothing." So what happens is the people respond to these five questions or items and for each question they have the following responses, which I've already input here into SPSS value labels: strongly disagree all the way through strongly agree, which gives us a 1 through 7 point scale for each question. So what we want to do here in our principal components analysis is we want to go ahead and analyze these five variables or items and see if we can reduce these five variables or items into one or a few components or factors which explain the relationship among the variables. So let's go ahead and start by running a correlation matrix and what we'll do is we're going to Analyze, Correlate, Bivariate, and then we'll move these five variables over. Go ahead and click OK and then here notice we get the correlation matrix of SWLS1 through SWLS5. So these are all the intercorrelations that we have here. And if we look at this off-diagonal where these ones here are the diagonal. And they're just a one because of variable is correlated with itself so that's always 1.0. And then the off-diagonal here represents the correlations of the items with one another. So for example this .531 here; notice it says in SPSS that the correlation is significant at the .01 level, two tailed. So this here is the correlation between SWLS2 and SLWS1. So all of these in this triangle here indicate the correlation between the different variables or items on the Satisfaction with Life Scale. And what we want to see here in factor analysis which we're about to run is that these variables are correlated with one another and at a minimum significantly so. Because what factor analysis or principal components analysis does is that it analyzes the correlations or relationships between our variables and basically we try to determine a smaller number of variables that can explain these correlations. So notice here we're starting with five variables, SWLS1 through five. Well hopefully in this analysis when we run our factor analysis we'll come out with one component that does a good job of explaining all these correlations here. And one of the key points of factor analysis is it's a data reduction technique. What that means is we enter a certain number of variables, like five in this example, or even 20 or 50 or what have you, and we hope to reduce those variables down to just a few; between one and let's say 5 or 6 is most of the solutions that I see. Now in this case since we have five variables we really want to reduce this down to 1 or 2 at most but 1 would be good in this case. So that's really a key point of factor analysis: we take a number of variables and we try to explain the correlations between those variables through a smaller number of factors or components and by doing that what we do is we get more parsimonious solution, a more succinct solution that explains these variables or relationships. And there's a lot of applications of factor analysis but one of the primary ones is when you're analyzing scales or items on a scale and you want to see how that scale turns out, so how many dimensions or factors doesn't it have to it.

Views: 58960
Quantitative Specialists

The factor analysis video series is availablefor FREE as an iTune book for download on the iPad. The ISBN is 978-1-62847-041-3. The title is "Factor Analysis". Waller and Lumadue are the authors. The iTune text provides accompanying narrative and the SPSS readouts used in the video series.
The book can be accessed at:
https://itunes.apple.com/us/book/factor-analysis/id656956844?ls=1
This video gives a brief introduction to factor analysis. Emphasis is placed on a visual representation of the process of data reduction. Groundwork is laid for the development of the other aspects of factor analysis.

Views: 82077
Lee Rusty Waller

The factor analysis video series is available for FREE as an iTune book for download on the iPad. The ISBN is 978-1-62847-041-3. The title is "Factor Analysis". Waller and Lumadue are the authors. The iTune text provides accompanying narrative and the SPSS readouts used in the video series.
The book can be accessed at:
https://itunes.apple.com/us/book/factor-analysis/id656956844?ls=1
This video provides a methodology for writing factor analysis research questions.

Views: 16799
Lee Rusty Waller

In confirmatory factor analysis the researcher specifies the number of factors which underlie a set of observed variables, together with the relationships between the observed variables and the factors.
For more methods resources see:
http://www.methods.manchester.ac.uk

Views: 7686
methodsMcr

What is FACTOR ANALYSIS? What does FACTOR ANALYSIS mean? FACTOR ANALYSIS meaning - FACTOR ANALYSIS definition - FACTOR ANALYSIS explanation.
Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license.
Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it is possible that variations in six observed variables mainly reflect the variations in two unobserved (underlying) variables. Factor analysis searches for such joint variations in response to unobserved latent variables. The observed variables are modelled as linear combinations of the potential factors, plus "error" terms. The information gained about the interdependencies between observed variables can be used later to reduce the set of variables in a dataset. Factor analysis originated in psychometrics and is used in behavioral sciences, social sciences, marketing, product management, operations research, and other fields that deal with data sets where there are large numbers of observed variables that are thought to reflect a smaller number of underlying/latent variables.
Factor analysis is related to principal component analysis (PCA), but the two are not identical. There has been significant controversy in the field over differences between the two techniques (see section on exploratory factor analysis versus principal components analysis below). Clearly though, PCA is a more basic version of exploratory factor analysis (EFA) that was developed in the early days prior to the advent of high-speed computers. From the point of view of exploratory analysis, the eigenvalues of PCA are inflated component loadings, i.e., contaminated with error variance.

Views: 10112
The Audiopedia

In this video you will learn the theory of Factor Analysis. Factor Analysis is a popular variable reduction techniques and is also use for exploring patter among the variables in a data
For Training & Study packs on Analytics/Data Science/Big Data, Contact us at [email protected]
Find all free videos & study packs available with us here:
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Views: 31040
Analytics University

http://www.ScienceBookMix.com
This is the summary of Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research by Marjorie A. Pett, Nancy R. Lackey, John J. Sullivan.

Views: 239
ScienceBookMix

Views: 6215
Marketing research and analysis

This is a video lecture for the virtual residency for the DM class at CWRU. This lecture covers the various types of variables, specification, and an intro to exploratory factor analysis.

Views: 54232
James Gaskin

This video provides a brief overview of how to use AMOS (structural equation modeling program) to carry out confirmatory factor analysis of survey scale items.
The data for this video can be downloaded at: https://drive.google.com/open?id=1_VM6wOnBfUbpmkLyLXByVqpz3UKnRYqs
Check out my blog at: https://mikesstatsblog.blogspot.com/

Views: 62655
Mike Crowson

An introduction to Two Way ANOVA (Factorial) also known as Factorial Analysis. Step by step visual instructions organize data to conduct a two way ANOVA. Includes a comparison with One Way ANOVA. Instructions on how to build a mean table.
Playlist on Two Way ANOVA
http://www.youtube.com/playlist?list=PLWtoq-EhUJe2TjJYfZUQtuq7a0dQCnOWp
Like us on: http://www.facebook.com/PartyMoreStudyLess
David Longstreet Professor of the Universe
Professor of the Universe: David Longstreet http://www.linkedin.com/in/davidlongstreet/
MyBookSucks.Com

Views: 264704
statisticsfun

In intelligence research, personality research and other research fields of psychology, factor analytic models are used to structurize the variables' jungle.
For example: To simplify the variable structure of a personality questionnaire several questions (items), that are supposed to measure the same construct are grouped to one (latent) factor (e.g. extraversion).
But does this group of items really measure extraversion? Maybe some of the items "load" on a different factor. And Maybe other aspects of the model have flaws as well...
How well a factor model fits the data can be examined by a confirmatory factor analysis.
Keywords:
Confirmatory Factor Analysis - Factor Analysis - Psychology - Statistics - Research Methods - Personality Psychology - Extraversion - Conscientiousness - Openness - Neuroticism - Agreeableness - Five Factor Model - Intelligence - Model fit - Model specification - model identification - estimation - loadings - model modification - maximum likelihood - Chi-squared test - degrees of freedom

Views: 7938
www.LearningPsychology.net

This is a model fit exercise during a CFA in AMOS. I demonstrate how to build a good looking model, and then I address model fit issues, including modification indices and standardized residual covariances. I also discuss briefly the thresholds for goodness of fit measures. For a reference, you can use:
Litze Hu & Peter M. Bentler (1999) Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling: A Multidisciplinary Journal, 6:1, 1-55

Views: 391029
James Gaskin

This is Lecture 7 from PIE TUTORS's Online Structural Equation Modeling Training Series.

Views: 10619
PIE TUTORS

Professor Patrick Sturgis, NCRM director, in the third (of three) part of the Structural Equiation Modeling NCRM online course.
This video is part of the online learning resources from the National Centre for Research Methods (NCRM). To access the supporting materials (presentation slides, datasets, recommended reading, links to related publications and resources) visit http://www.ncrm.ac.uk/resources/online/SEM2016/

Views: 23394
NCRMUK

This video is first in series. Here I shall discuss the Factor Analsyis in detail, how factors are computed? what is meant by Communalities as well as Eigen Values?
PPT: https://docs.google.com/presentation/d/1CYpY8_-VbdZeF9OYTdNuP0VJ28OD2smy4ta-wDadVNQ/edit?usp=sharing

Views: 19166
Neeraj Kaushik

Introduction to factor analysis/ principal components analysis including interpretation.
Do I need to run a factor analysis (FA)?
Questionnaires with inter-related questions, summarising content of lots of questions (items) by a few factors, creating scores for attributes, validity of a scale, checking a scale is unidimensional for Cronbach Alpha
Types of FA: exploratory and confirmatory
Steps in perfoming EFA
Example: EFA on personaility data
NOTE: somewhere in the video I say you can compute mean and standard deviations of the estimated factor scores. Well, you can, but it;s not meaningful. To see how people scored on a factor, a histogram or QQ plot would do.

Views: 65274
Phil Chan

This video covers factor (component) loadings in factor analysis.
Click here for free access to all of our videos: https://www.youtube.com/user/statisticsinstructor
(Remember to click on "Subscribe")
factor loadings
component loadings
factor analysis

Views: 6719
Quantitative Specialists

Applied Multivariate Statistical Modeling by Dr J Maiti,Department of Management, IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in

Views: 7439
nptelhrd

In this video I demonstrate how to do a factor analysis in SmartPLS for either a formative or reflective measurement model.
I now have an article published that cites this video.
Paul Benjamin Lowry and James Gaskin (2014). "Partial least squares (PLS)structural equation modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it," IEEE Transactions on Professional Communication (57:2), pp. 123-146.
http://www.kolobkreations.com/PLSIEEETPC2014.pdf

Views: 78449
James Gaskin

This video provides a strategy for obtaining a matrix of polychoric correlations from LISREL to perform factor analysis on ordinal variables in SPSS. You can obtain a free student version of LISREL here: http://www.ssicentral.com/lisrel/student.html
You can obtain a copy of the data used in the video here: https://drive.google.com/open?id=1n9SnVnBe1G7iGV8bYS-8CAV1gzbcbLZA
You can download a copy of the SPSS syntax file used in the video here: https://drive.google.com/open?id=1bh_QGikepMju6ArwEeqomELPyrs0iJNh
For further info on the approach to performing factor analysis in SPSS on matrix input data, you can go here: http://www-01.ibm.com/support/docview.wss?uid=swg21479694
For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below:
Introductory statistics:
https://sites.google.com/view/statisticsfortherealworldagent/home
Multivariate statistics:
https://sites.google.com/view/statistics-for-the-real-world/home

Views: 869
Mike Crowson

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.

Views: 1593
Curran-Bauer Analytics

Principal Component Analysis and Factor Analysis
https://sites.google.com/site/econometricsacademy/econometrics-models/principal-component-analysis

Views: 83096
econometricsacademy

This video illustrates how you can utilize the FACTOR program/application (download at http://psico.fcep.urv.es/utilitats/factor/Download.html) to run PCA and factor analysis using the Polychoric correlation matrix option

Views: 4160
Mike Crowson

Links of Data set and case study used in the above video.
1.https://drive.google.com/open?id=1WzUf0rJU87nAZQ-ckf_X6w8FGpNB-srE

Views: 4382
Dr. Shailesh Kaushal

This video demonstrates conducting a factor analysis (principal components analysis) with varimax rotation in SPSS.

Views: 76929
Dr. Todd Grande

Links of Data set and case study used in the above video.
1.https://drive.google.com/open?id=1L-rNjsWuLE39AUOrj-O-2ugWX0-t0oum

Views: 5754
Dr. Shailesh Kaushal

-Introduction to factor analysis
-Factor analysis vs Principal Component Analysis (PCA) side by side
Read in more details - https://www.udemy.com/principal-component-analysis-pca-and-factor-analysis/?couponCode=GP_TR_1

Views: 6809
Gopal Malakar

Subject : Psychology
Paper : Applied Psychometrics

Views: 318
Vidya-mitra

Video introduces how to fit CFA models in Amos. The example involves a five factor measure of personality. A five factor uncorrelated and a five factor uncorrelated model are fit. The use of modification indices is also demonstrated.

Views: 34587
Jeromy Anglim

This is Lecture 7 from PIE TUTORS's Online Structural Equation Modeling Training Series.
This video is brought to you by:-
PIE TUTORS
a statistical consulting and data analysis consultancy for scholars and researchers
Visit us at : www.pietutors.com
YouTube : www.youtube.com/pietutors
Facebook : https://www.facebook.com/pietutors.yourstatisticalpartner
Email : [email protected]
Contact : +91 895 567 8210

Views: 27324
PIE TUTORS

Overview of exploratory factor analysis steps http://screenr.com/Pgg

Views: 1974
James Neill

Video provides an overview of how to use the Stata 14.1 GUI when testing CFA models and path analysis models (with latent variables)
You can download a copy of the data and follow along: https://drive.google.com/open?id=1kwK9_l2f0q2leHgH3SLAHbAAbHX0ECUq
A copy of the file containing the CFA model can be downloaded here: https://drive.google.com/open?id=1bCDeitOapvZ-tlEGKlH1f_DVCPBBL8sL
For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below:
Introductory statistics:
https://sites.google.com/view/statisticsfortherealworldagent/home
Multivariate statistics:
https://sites.google.com/view/statistics-for-the-real-world/home

Views: 15764
Mike Crowson

Applied Multivariate Statistical Modeling by Dr J Maiti,Department of Management, IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in

Views: 35123
nptelhrd

This video tutorial will show you how to conduct an Exploratory factor analysis in R. This is an intermediate level video. You should know how to read data into R, conduct and understand PCA before watching this video.

Views: 39042
Ed Boone

Newest video on CFA using the AMOS program. The data for this illustration can be downloaded at:
https://drive.google.com/open?id=1_VM6wOnBfUbpmkLyLXByVqpz3UKnRYqs
For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below:
Introductory statistics:
https://sites.google.com/view/statisticsfortherealworldagent/home
Multivariate statistics:
https://sites.google.com/view/statistics-for-the-real-world/home

Views: 9289
Mike Crowson

This video covers the types of rotation in a factor analysis, including orthogonal (uncorrelated) and oblique (correlated) rotation.
orthogonal rotation in factor analysis
oblique rotation in factor analysis
Factor Analysis, Principal Components Analysis, Rotation, Methods of rotation, oblique rotation, orthogonal rotation, Varimax, Oblimin, Quartimax, Equamax

Views: 2304
Quantitative Specialists

In this video I demonstrate how to input matrix summary data into SPSS to run an exploratory factor analysis. I demonstrate how to do this using summary data published in Bear et al. (2010). You can obtain a copy of the syntax file used in this video here: https://drive.google.com/open?id=1AoUDRtMFFFou2YzLPBwv6bSsIZVtXvl4
Additional info on using matrix input in SPSS analyses (albeit demonstrated using regression) can be found at the following links:
https://www.youtube.com/watch?v=_c1wqGteXwc&feature=youtu.be
http://core.ecu.edu/psyc/wuenschk/SPSS/CorrMatrix_Input2SPSS.pdf
http://www.spsstools.net/en/syntax/syntax-index/regression-repeated-measures/regression-with-correlation-matrix-as-input/
For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below:
Introductory statistics:
https://sites.google.com/view/statisticsfortherealworldagent/home
Multivariate statistics:
https://sites.google.com/view/statistics-for-the-real-world/home

Views: 241
Mike Crowson

In this video you will learn how to perform Exploratory Factor Analysis in SAS. EFA is used for exploring data in terms of finding pattern among the variables. It is also a variable reduction technique
For Training & Study packs on Analytics/Data Science/Big Data, Contact us at [email protected]
Find all free videos & study packs available with us here:
http://analyticuniversity.com/
SUBSCRIBE TO THIS CHANNEL for free tutorials on Analytics/Data Science/Big Data/SAS/R/Hadoop

Views: 11909
Analytics University

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© 2018 Market leader intermediate business english course book david cotton

The investment world is changing constantly, which means you must update your knowledge continually. Rather than being satisfied with what you already know, keep on learning . Tools and tips. Investment Portfolio Management. Investment Portfolio Management is the art of putting together and managing various investments to meet specific goals. We will examine management strategy choices, asset allocation and investing strategies, and management of risk as they pertain to management of an investment portfolio. Management Strategies. Passive Management. Passive management is for investors willing to accept market returns. Using a fixed asset allocation with a portfolio comprised of index funds would be examples of passive management. Active Management. Asset Allocation Strategies. Strategic Asset Allocation.