Structural equation models | Factor analysis
In statistics, confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social research. It is used to test whether measures of a construct are consistent with a researcher's understanding of the nature of that construct (or factor). As such, the objective of confirmatory factor analysis is to test whether the data fit a hypothesized measurement model. This hypothesized model is based on theory and/or previous analytic research. CFA was first developed by JΓΆreskog (1969) and has built upon and replaced older methods of analyzing construct validity such as the MTMM Matrix as described in Campbell & Fiske (1959). In confirmatory factor analysis, the researcher first develops a hypothesis about what factors they believe are underlying the measures used (e.g., "Depression" being the factor underlying the Beck Depression Inventory and the Hamilton Rating Scale for Depression) and may impose constraints on the model based on these a priori hypotheses. By imposing these constraints, the researcher is forcing the model to be consistent with their theory. For example, if it is posited that there are two factors accounting for the covariance in the measures, and that these factors are unrelated to each other, the researcher can create a model where the correlation between factor A and factor B is constrained to zero. Model fit measures could then be obtained to assess how well the proposed model captured the covariance between all the items or measures in the model. If the constraints the researcher has imposed on the model are inconsistent with the sample data, then the results of statistical tests of model fit will indicate a poor fit, and the model will be rejected. If the fit is poor, it may be due to some items measuring multiple factors. It might also be that some items within a factor are more related to each other than others. For some applications, the requirement of "zero loadings" (for indicators not supposed to load on a certain factor) has been regarded as too strict. A newly developed analysis method, "exploratory structural equation modeling", specifies hypotheses about the relation between observed indicators and their supposed primary latent factors while allowing for estimation of loadings with other latent factors as well. (Wikipedia).
Find the value of the trigonometric expression using inverse
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Tutorial for how to evaluate for the composition of two trigonometric functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
JASP 0.14 Tutorial: Confirmatory Factor Analysis (CFA) (Episode 30)
EDIT/CORRECTION: There's an error in my description of the chi-square model fit outcome. I state that it is good that the p-value is very small and reflects a good model fit. As mentioned by a keen viewer, this chi-square application is the opposite for other NHST outcomes. Here, a signifi
From playlist JASP Tutorials
Confirmatory factor analysis in AMOS | Part 1
In this video, I demonstrate how to use AMOS for confirmatory factor analysis (CFA). For a discussion on normality analysis, please see the following videos: #1: https://www.youtube.com/watch?v=1gSyZ_DPQRQ #2: https://www.youtube.com/watch?v=uCjOoEKQJvo AMOS (trial version) can be downlo
From playlist Structural Equation Modeling
A selective survey of selective inference β Jonathan Taylor β ICM2018
Probability and Statistics Invited Lecture 12.9 A selective survey of selective inference Jonathan Taylor Abstract: It is not difficult to find stories of a crisis in modern science, either in the popular press or in the scientific literature. There are likely multiple sources for this c
From playlist Probability and Statistics
R - SEM - Confirmatory Factor Analysis Class Assignment
Recorded: Summer 2015 Lecturer: Dr. Erin M. Buchanan Packages needed: lavaan, semPlot Class assignment for structural equation modeling. Topic covers how program a confirmatory factor analysis (CFA), heywood cases, fit indices, loadings, residuals, modification indices, and model comparis
From playlist Structural Equation Modeling
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
R - Confirmatory Factor Analysis Lecture
Lecturer: Dr. Erin M. Buchanan Spring 2021 https://www.patreon.com/statisticsofdoom This video covers the basics of confirmatory factor analysis or measurement models. You will learn about how to build, analyze, summarize, and diagram a measurement model in lavan. You can learn more at:
From playlist Structural Equation Modeling 2020
R - Confirmatory Factor Analysis Lecture
Lecturer: Dr. Erin M. Buchanan Missouri State University Summer 2016 This lecture video covers the background to confirmatory factor analysis - identification, scaling, fit indices, and how to interpret parameters. Lecture materials and assignment available at statisticsofdoom.com. htt
From playlist Structural Equation Modeling
Structural equation modeling using AMOS
In this video, I demonstrate how to conduct a structural equation modeling (SEM) analysis in AMOS. As SEM is based on confirmatory factor analysis (CFA), I would suggest you watch the following videos: Video 1: https://www.youtube.com/watch?v=HKs9vIkpIXE&list=PLTjlULGD9bNLPjpFqDlVMFu0GyN
From playlist Structural Equation Modeling
Evaluating the composition of inverse functions
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
R - Multigroup CFA with lavaan Example
Lecturer: Dr. Erin M. Buchanan Harrisburg University of Science and Technology Fall 2019 This video updates the older version of the multigroup confirmatory factor analysis examples. This version uses a newer package and shows you how to complete the steps of a multigroup analysis even if
From playlist Structural Equation Modeling
Latent Growth Curve Modeling | Part 2 | Structural Equation Modeling
In the second installment of this video series, I will discuss the essential concepts in Growth Curve Modeling within the Structural Equation Modeling framework.
From playlist Growth Curve Models
Evaluating the composition of inverse functions trigonometry
π Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
R - Exploratory Factor Analysis Lecture
Lecturer: Dr. Erin M. Buchanan Fall 2020 https://www.patreon.com/statisticsofdoom This video is part of my structural equation modeling class - you will learn how to perform an exploratory factor analysis as a way to ease into the ideas of SEM. You will learn how to assess the number of
From playlist Structural Equation Modeling 2020