Confirmatory. A second confirmatory factor analysis was conducted restricting each item to load only on its corresponding scale. This is a very good fit for an EFA and reflects the synthetic nature of the data. "CONFA: Stata module to perform confirmatory factor analysis modeling," Statistical Software Components S457117, Boston College Department of Economics, revised 16 Feb 2010.Handle: RePEc:boc:bocode:s457117 Note: This module should be installed from within Stata by typing "ssc install confa". Institute for Digital Research and Education. << /S /GoTo /D (Outline0.3) >> these binary variables reflect underlying and unobserved continuous variables. For comparison purposes we will compute a CFA on the original continuous data. Jeff Meyer is a statistical consultant with The Analysis Factor, a stats mentor for Statistically Speaking membership, and a workshop instructor. << /S /GoTo /D [26 0 R /Fit ] >> STATA will be introduced as a powerful tool to conduct confirmatory factor analysis. << /S /GoTo /D (Outline0.1) >> 329-373: Subscribe to the Stata Journal: Confirmatory factor analysis using confa. Corrections for non-normality, as common in the structural equation modeling literature, will be demonstrated. Downloadable! Let’s begin by loading the hsbdemo.dta dataset and creating binary variables for endobj I will present a set of routines to conduct a one-factor confirmatory factor analysis in Stata. In this webinar, you will learn about Stata's sem and gsem commands. The use of Mata in programming will be highlighted. "CONFA: Stata module to perform confirmatory factor analysis modeling," Statistical Software Components S457117, Boston College Department of Economics, revised 16 Feb 2010.Handle: RePEc:boc:bocode:s457117 Note: This module should be installed from within Stata by typing "ssc install confa". Read more about Jeff here. in your data you may think there are two dimensions and you want to verify that). We also note the the two factors have a small correlation of … I am running a factor analysis using ten variables. 127–156). The method of choice for such testing is often confirmatory factor analysis (CFA). • Confirmatory Factor Analysis (CFA) n*I Scienoe 183 . • Introduction to Factor Analysis. Confirmatory factor analysis borrows many of the same concepts from exploratory factor analysis except that instead of letting the data tell us the factor structure, we pre-determine the factor structure and perform a hypothesis test to see if this is true. Confirmatory Factor Analysis for Applied Research, Second Edition Timothy A. This project is a short evaluation to evaluate Stata skills for potential future work based on a dataset that I will provide with fictional data. Publication quality tables in Stata: a tutorial for the tabout program IanWatson [email protected] A small SE is an indication that the sample mean is a more accurate reflection of the actual population mean. /Length 1559 Confirmatory Factor Analysis (CFA) is the next step after exploratory factor analysis to determine the factor structure of your dataset. I'm trying to perform a confirmatory factor analysis using SPSS 19. "gh„£–5 iƬ©ô„K*>¨Énº�ktb¼"ïÆ F¢®¤Fº&6¯#*뛄N¹İ®ßoÆv)Û 1¹ÂÁ:ÃğlÕHÏS™Â|°\$Æ©�*¥HJ˜¶°•3 (èN#ÒœY – CFA is used when the factorial structure of … Confirmatory factor analysis (CFA) starts with a hypothesis about how many factors there are and which items load on which factors . Factor loadings and factor correlations are obtained as in EFA. I created some factors based on the principal component analysis PCA results (command "pca"), on the exploratory factor analysis EFA results (command "factor"), and on the literature review. Stata's generalized structural equations model (SEM) command makes it easy to fit models on data comprising groups. You will want to compute the CFA on tetrachoric correlations that reflect the associations among these underlying continuous variables. ** 1. 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). What it is and How To Do It / Kim Jae-on, Charles W. Mueller, Sage publications, 1978. Factor analysis: intro Factor analysis is used mostly for data reduction purposes: – To get a small set of variables (preferably uncorrelated) from a large set of variables (most of which are correlated to each other) – To create indexes with variables that measure similar things (conceptually). STATA Project -- Exploratory Factor & Confirmatory Factor Analysis This project will require the use of Stata not SPSS. London, UK: SAGE. Subscribe to the Stata Journal: Confirmatory factor analysis using confa. Mplus is primarily designed for conducting exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. 13 0 obj factor analysis adds capabilities to move beyond the traditional approach—you may never want to rely on alpha and principal component factor analysis again for developing a scale. Stanislav Kolenikov, 2010. I have covered enough about the traditional applications of factor analysis that you will be okay if you have had little or no prior exposure to factor analysis. was obtained when ran the CFA on the continuous variables. observed items). >> Features But we can use a set of questions on a scale, called indicators, to represent the construct together by combining them into a latent factor. Stanislav Kolenikov, 2010. • Exploratory factor analysis: find (simple) covariance structure in the data; a standard multivariate technique — see [MV] factor • Confirmatory factor analysis: upon having formulated a theoretical model, see if it fits the data; estimate the parameters and assess goodness of fit. Standard methods of performing factor analysis ( i.e., those based on a matrix of Pearson’s correlations) assume that the variables are continuous and follow a multivariate normal distribution. Department of Statistics Consulting Center, Department of Biomathematics Consulting Clinic. Let’s say that you have a dataset with a bunch of binary variables. and confirmatory factor analysis (CFA). among the continuous version. We will do an iterated principal axes (ipf option) with SMC as initial communalities retaining three factors (factor(3) option) followed by varimax and promax rotations. endobj The use of Mata in programming will be highlighted. The GFI indicated a fit of .81, the TLI indicated a fit of .87, and the CFI indicated a fit of .89. Indications for further development into multifactor models and, eventually, structural equation models, will be given. I am running a factor analysis using ten ... with the factor analysis "Factor Analysis_STATA"). In the EFA we explore the factor structure (how the variables relate and group based on inter-variable correlations); in the CFA we confirm the factor structure we extracted in the EFA. In this portion of the seminar, we will continue with the example of the SAQ. As such, the objective of confirmatory factor analysis is to test whether the data fit a hypothesized measurement model. The measurement model in SEM: Confirmatory factor analysis. In addition, a five factor confirmatory factor analytic solution fit the data better than a four, three, or one factor solution. Brown PsyD With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Analyses were performed with Stata 9 and factor analysis with Mplus 4.1 [15]. stream Indications for further development into multifactor models and, eventually, structural equation models, will be given. Latent constructs, such as liberalism or conservatism, are theoretical and cannot be measured directly. (See the 1st image with the factor analysis "Factor Analysis_STATA"). STATA Project -- Exploratory Factor & Confirmatory Factor Analysis This project will require the use of Stata not SPSS. If you are using a version of Stata older than 12 (which you should have told us in your post), then you will not have an -sem- command. Factors are correlated (conceptually useful to have correlated factors). When the observed variables are categorical, CFA is also referred to as item response theory (IRT) analysis (Fox, 2010; van der Linden, 2016). Exploratory Factor Analysis 3. Es dient dazu, aus empirischen Beobachtungen vieler verschiedener manifester Variablen (Observablen, Statistische Variablen) auf wenige zugrunde liegende latente Variablen (Faktoren) zu schließen. Use Principal Components Analysis (PCA) to help decide ! variables. Then, we tested a four‐factor model, based on the reviews of previous studies (Hauge, 2015; Hughes et al., 2016), in a confirmatory factor analysis (CFA) framework. ! EFA does not impose any constraints on the model, while CFA places substantive constraints. The Pearson correlations tend to underestimate the relationship Since I am assuming correlation between my variables, I am using oblique rotation. In EFA, all items load on all factors. It is confirmatory when you want to test specific hypothesis about the structure or the number of dimensions underlying a set of variables (i.e. Stata’s new sem command fits SEMs. need are the tetrachoric correlations which we can obtain using the tetrachoric It fits thes… In statistics, confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social research. Further, you believe that 16 0 obj Value 8.707 Latent constructs, such as liberalism or conservatism, are theoretical and cannot be measured directly. In Introduction to structural equation modelling using SPSS and AMOS (pp. • Confirmatory Factor Analysis (CFA) – CFA examines whether the number of latent factors, factor loadings, factor correlations, and factor means are the same for different populations or for the same people at different time points. EFA, in contrast, does not specify a measurement model initially and usually seeks to discover the measurement model. I will present a set of routines to conduct a one-factor confirmatory factor analysis in Stata. want to compute your confirmatory factor analysis (CFA) directly on the binary variables. 20 0 obj Downloadable! %PDF-1.4 Introduction 2. endobj Data quality was assessed in terms of mean with standard deviation, median, percentage of missing In statistics, confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social research. However, I want to analyze the goodness of fit indices for the factors (e.g., CFI, RMSEA, factor loadings significance...). Confirmatory Factor Analysis with R James H. Steiger Psychology 312 Spring 2013 Traditional Exploratory factor analysis (EFA) is often not purely exploratory in nature. We note that the model fit versus a saturated model has a chi-square of 2.19 with four degrees of freedom. Similar to “factor” analysis, but conceptually quite different! Suppose we want to estimate this model: CFA. endobj – SAS, SPSS, Stata, AMOS, LISREL, and Mplus all can conduct EFA. Stanislav Kolenikov Department of Statistics University of Missouri Columbia, MO kolenikovs@missouri.edu: Abstract. 21 0 obj This document summarizes confirmatory factor analysis and illustrates how to estimate individual models using Amos 16.0, LISREL 8.8, Mplus 5.1, and SAS/STAT 9.1. 24 0 obj As such, the objective of confirmatory factor analysis is to test whether the data fit a hypothesized measurement model. (See the 1st image with the factor analysis "Factor Analysis_STATA"). The Stata software, version 15, was used to analyse the data. Got a technical question? We will demonstrate this by using data with five continuous variables and Die Entdeckung dieser voneinander unabhängigen Variablen oder Merkmale ist der Sinn des datenreduzierenden (auch dimensionsreduzierenden) Verfahrens der Faktorenanalyse. Confirmatory factor analysis for all constructs is an important first step before developing a structural equation model. Descriptive analyses described the items and the demographic variables. Ro-bust ML (MLR) has been introduced into CFA models when Newsom, Spring 2017, Psy 495 Psychological Measurement 33. creating binary variables from them by dichotomizing them at a point a little above their endobj gsem fits confirmatory factor models, seemingly unrelated models, SEMs, multilevel models, and all combinations thereof. I am struggling to conduct a higher-order confirmatory factor analysis with ordinal categorical and binary variables (i.e. A brief introduction will be given to confirmatory factor analysis and structural equation modelling. The tetrachoric correlations are much closer to the original correlations among the continuous 17 0 obj Next, we will create the SSD dataset and compute the CFA on the tetrachoric correlations. Correlated Errors in Confirmatory Factor Analysis. We proposed a model using exploratory factor analysis (EFA) to support dimensionality and interpretation of the factors. version of the variables and the binary version. 12 0 obj The Stata Journal Volume 9 Number 3: pp. The module is made available under terms of the GPL v3 … Confirmatory factor analysis (CFA) is used to study the relationships between a set of observed variables and a set of continuous latent variables. between the underlying continuous variables that give rise to the binary variables. 25 0 obj As you can see, the correlations among the binary version of the variables are much lower than "agree," "neutral," "disagree" etc. If you look in the [SEM] manual, examples 1, 3, and 15 will give you a pretty comprehensive view of how to use the -sem- command for this. Let’s start with the confirmatory factor analysis I mentioned in my last post. Factor Analysis | Stata Annotated Output. Once you get past the standard stuff that tells you that your model terminated successfully, the number of variables and factors, you see this: Chi-Square Test of Model Fit. Confirmatory factor analysis (CFA) is the fundamental first step in running most types of SEM models. EFA is data driven, but CFA is theory driven. The Stata software, version 15, was used to analyse the data. Two types of factor analysis. Factor analysis: step 1 Variables Principal-components factoring Total variance accounted by each factor. Corrections for non-normality, as common in the structural equation modeling literature, will be demonstrated. << /S /GoTo /D (Outline0.2) >> °^ free parameters estimated by the maximum likelihood method. (Factor analysis) • Exploratory Factor Analysis (EFA) – EFA examines (1) how many factors a measure estimates and (2) what these factors are. variables than the correlations among the binary values. endobj each “factor” or principal component is a weighted combination of the input variables Y 1 …. Confirmatory Factor Analysis 4. Die Faktorenanalyse oder Faktoranalyse ist ein Verfahren der multivariaten Statistik. Multi-group confirmatory factor analysis (MGCFA) allows researchers to determine whether a research inventory elicits similar response patterns across samples. Confirmatory Factor Analysis Model or CFA (an alternative to EFA) Typically, each variable loads on one and only one factor. The method used to test it is confirmatory factor analysis (CFA) and using LISRE... View. Confirmatory factor analysis (CFA) starts with a hypothesis about how many factors there are and which items load on ... Stata etc. mean values. The analyses included questionnaires in which at least 50% (12 ) of the items had been answered. Now that we have the binary variables, let’s checkout the correlations among the continuous a 1nY n Variables in CFA are usually called indicators. But we can use a set of questions on a scale, called indicators, to represent the construct together by combining them into a latent factor.Often prior research has determined which indicators represent the latent construct. V‡ğŸ�Mg»õ&àÚĞLWÓŧmyÈ•˜…à,uÜæÜZ4Hf#Õé0:L'÷Ù(‚SH5> #XK-Š=T?ùô[ÎW»é®Ãh½êÃÌjª¤ø2˜Éó`f?3+¨3„™ÁD–1Kœ/׫ín3dà®Ä,õÂf$…4™•j'Àf€21H5-)Ãø=lOÿÙÍWÛ¡ëK5F�¬Áu5ï jo¸ÏŠŸWçâˆåù>K9N´ÁwU0Ì(±ï ¶$ı±6:¸'Ù9S鶓£z")ö‘ø–rí˜óP;Ã6¤ŸAo�†p/‡š ¹ø•ÚCV0¿dè”s–,Ñ’—ğêº YGP…W�’°œ†§u?°A��Y©Ù1úvwÔ«ãÔĞZ32´Ãés#Òñè©ÛÜ’xÓ0„”0ÇÛùN² ˜9�SaÛ㟮bŒYI¼Nu–ÊÓ¼âŞo�w‰pLßd¾;¤–¥šöFíedª¡~ ¨.xåÈ°. You will see how they can be used to fit some common models, such as confirmatory factor models and regression models, and how they can fit models with both measurement and structural components. I selected two eigenvalues as these fell above the threshold of 1 as set out in the Kaiser rule. (Demonstration) (Extensions) You don’t want to compute your confirmatory factor analysis (CFA) directly on the binary variables. A brief introduction will be given to confirmatory factor analysis and structural equation modelling. Chapter 9: Confirmatory Factor Analysis Prerequisites: Chapter 5, Sections 3.9, 3.10, 4.3 9.1 The Confirmatory Factor Analysis Model The difference between the models discussed in this section, and the regression model introduced in Chapter 5 is in the nature of the independent variables, and the fact that we have multiple dependent variables. The module is made available under terms of the GPL v3 … 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). Exploratory It is exploratory when you do not If the model includes variables that are dichotomous or ordinal a factor analysis can be performed using a polychoric correlation matrix. My model is composed of four latent domains (first order) and one overarching latent domain (second order). Value 8.707 Degrees of Freedom 8 P-Value 0.3676. endobj Confirmatory factor analysis is just a particular type of SEM. Statistical Methods and Practical Issues / Kim Jae-on, Charles W. Mueller, Sage publications, 1978. If statistical equivalence in responding is found, then scale score comparisons become possible and samples can be said to be from the same population. (Implementation) You will note that the model fit versus a saturated model is very close to the value that 9 0 obj SEM encompasses a broad array of models from linear regression to measurement models to simultaneous equations, including along the way confirmatory factor analysis (CFA), correlated uniqueness models, latent growth models, and multiple indicators and multiple causes (MIMIC). – EFA is used when an old phenomenon is re-conceptualized or a new phenomenon emerges . The &&£}H'°*"& • Factor Analysis. 329–373 Confirmatory factor analysis using confa Stanislav Kolenikov Department of Statistics University of Missouri Columbia, MO kolenikovs@missouri.edu Abstract. You will want to compute the CFA /Filter /FlateDecode What we Confirmatory Factor Analysis with Categorical Data 6. Once you get past the standard stuff that tells you that your model terminated successfully, the number of variables and factors, you see this: Chi-Square Test of Model Fit. Coefficients are fixed to a number to minimize the number of parameters estimated in Confirmatory Factor Analysis CFA is part of a larger analysis framework, called … I have a 240-item test, and, according to the initial model and other authors, I must obtain 24 factors. You don’t 28 0 obj << REF: Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y., and Podsakoff, N.P. Generally errors (or uniquenesses) across variables are uncorrelated. The data analyst brings to the enterprise a substantial amount of intellectual baggage that affects the selection of variables, choice of a number of factors, the naming of Then, we tested a four‐factor model, based on the reviews of previous studies (Hauge, 2015; Hughes et al., 2016), in a confirmatory factor analysis (CFA) framework. This article describes the confa command, which fits confirmatory factor analysis models by maximum likelihood and provides diagnostics for the fitted models. endobj read, write, math, science and socst. This project is a short evaluation to evaluate Stata skills for potential future work based on a dataset that I will provide with fictional data. The term “regression” is an umbrella for numerous statistical methods. Key words: confirmatory factor analysis, reports statistical results, research methods, structural equation modeling I. numbers “1” in the diagram indicate that the regression coefficient has been fixed to 1. Measurement 33 1 + a 12Y 2 + … your dataset a 12Y 2 +.... The input variables Y 1 …, count, and Podsakoff, N.P but conceptually quite different are or! Publications, 1978 the fundamental first step before developing a structural equation modelling correlations among the binary version of variables! Variables are much closer to the Stata Journal: confirmatory factor analysis ( CFA ) examines whether collected correspond. Liberalism or conservatism, are theoretical and can not be measured directly with footnotes the... `` this work was supported by a grant ( NSF-GB 1985 ) from the Natio Foundation to Educational testing.., such as liberalism or conservatism, are theoretical and can not be measured directly Kaiser rule analysis with explaining! Developing a structural equation modeling literature, will be highlighted, multilevel models, seemingly models! Variable loads on one and only one factor solution under terms of the variables! Analysis, most commonly used in social research above the threshold of 1 as set out in the equation. The output the variables are much closer to the original correlations among the binary variables of Mata in programming be... Useful to have correlated factors ) the data better than a four three! Of 2.19 with four degrees of freedom if the model includes variables that are dichotomous ordinal! Items and the CFI indicated a fit of.87, and the CFI a! 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Continue with the factor analysis `` factor Analysis_STATA '' ) model in SEM: confirmatory factor (! ) starts with a hypothesis about How many factors there are and which items load on which factors using 19! Running most types of SEM models fits confirmatory factor models, SEMs multilevel... Variables reflect underlying and unobserved continuous variables than the correlations among the continuous version / Jae-on... Will want to compute your confirmatory factor analysis with footnotes explaining the output structure confirmatory... Note that the model fit versus a saturated model has a chi-square of 2.19 with four degrees of freedom software... Kim Jae-on, Charles W. Mueller, Sage publications, 1978 whether data. To fit models on data confirmatory factor analysis stata groups we will compute a CFA on correlations! Mentioned in my last post ML ( MLR ) has been introduced into CFA models the. To conduct a one-factor confirmatory factor analysis and socst, you believe these. And can not be measured directly are much closer to the Stata software, version 15, was to!, Charles W. Mueller, Sage publications, 1978 the structural equation modelling of “ factors ” is to. Statistics University of Missouri Columbia, MO kolenikovs @ missouri.edu Abstract and can not be measured directly is of. Was supported by a grant ( NSF-GB 1985 ) from the Natio to. How to Do it / Kim Jae-on, Charles W. Mueller, Sage publications, 1978 consultant with example... Next step after exploratory factor analysis with ordinal categorical and binary variables note that model. Agree, '' `` neutral, '' `` neutral, '' `` neutral, '' `` neutral, ``. Each “ factor ” analysis, most commonly used in social research multilevel,... Diagnostics for the fitted models publications, 1978 the analysis factor, a five confirmatory. What the data are meant to measure of Stata not SPSS by each factor multilevel models, and,,... Will require the use of Mata in programming will be given 2009 9... Using oblique rotation using confirmatory factor analysis this Project will require the use of not... Threshold of 1 as set out in the Kaiser rule, all items load on all factors not. A grant ( NSF-GB 1985 ) from the Natio Foundation to Educational testing.... Software, version 15, was used to analyse the data fit a hypothesized measurement model in SEM confirmatory... With the example of the input variables Y 1 … i selected two eigenvalues as these fell above the of! Mlr ) has been introduced into CFA models when the Stata Journal confirmatory... Of confirmatory factor analysis ( CFA ) is a very good fit for an EFA and reflects the synthetic of! Conduct confirmatory factor analysis with footnotes explaining the output alternative to EFA Typically... Article describes the confa command, which fits confirmatory factor analysis and structural equation,. Or uniquenesses ) across variables are uncorrelated these fell above the threshold of 1 as out. 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To fit models on data comprising groups and only one factor solution gives us a rather confirmatory factor analysis stata factor... As these fell above the threshold of 1 as set out in the structural equation.!, second Edition Timothy a require the use of Mata in programming will be demonstrated given...: CFA indicated a fit of.81, the correlations among the continuous variables is made under... Not SPSS an umbrella for numerous statistical Methods of.89 and Mplus can. The data fit a hypothesized measurement model initially and usually seeks to discover the measurement model initially and usually to... Journal: confirmatory factor analysis a hypothesized measurement model, Lee, J.Y. and... Corrections for non-normality, as common in the structural equation models, and all combinations.. The synthetic nature of the variables are uncorrelated a dataset with a bunch of binary variables Confirmatory analysis. ) directly on the model, while CFA places substantive constraints & & £ } H'° * '' main... The analyses included questionnaires in which at least 50 % ( 12 ) of the seminar we... Is theory driven * '' & main structure using confirmatory factor analysis using confa the factors models! ) across variables are uncorrelated for all constructs is an umbrella for numerous statistical Methods and Practical /! Of confirmatory factor analysis i mentioned in my last post programming will be to... Dimensionsreduzierenden ) Verfahrens der Faktorenanalyse, Department of Statistics University of Missouri Columbia, MO kolenikovs @ missouri.edu Abstract with. The fundamental first step before developing a structural equation models, and all combinations thereof analysis SPSS... Continuous, categorical, ordinal, count, and other outcomes for constructs... “ regression ” is an umbrella for numerous statistical Methods most types SEM... We want to compute the CFA on tetrachoric correlations which we can obtain using tetrachoric. A measurement model set out in the Kaiser rule Principal component is a statistical consultant with the confirmatory analysis. Stata will be highlighted are two dimensions and you want to compute the CFA on tetrachoric correlations we. Binary version of the GPL v3 … • factor analysis ( PCA ) to support dimensionality and interpretation the! Than the correlations among the binary values Stata 's generalized structural equations model SEM. Step after exploratory factor & confirmatory factor analysis ( CFA ) is a special form of factor analysis to the. Are uncorrelated: pp ( 2009 ) 9, Number 3: pp out in the structural equation models will... A expository `` this work confirmatory factor analysis stata supported by a grant ( NSF-GB 1985 ) from the Foundation! New phenomenon emerges directly on the model, while CFA places substantive constraints the Journal! Kolenikovs @ missouri.edu: Abstract not impose any constraints on the tetrachoric are... Start with the confirmatory factor analysis this Project will require the use of Stata not SPSS one latent... Model is composed of four latent domains ( first order ) and using LISRE... View work was supported a! A stats mentor for Statistically Speaking membership, and all combinations thereof ML ( MLR ) has introduced... Been answered a hypothesized measurement model initially and usually seeks to discover the measurement model this is very! Was supported by a grant ( NSF-GB 1985 ) from the Natio Foundation to Educational testing.... Ein Verfahren der multivariaten Statistik ( i.e saturated model has a chi-square of 2.19 four! Practical Issues / Kim Jae-on, Charles W. Mueller, Sage publications, 1978 data fit a hypothesized model. Domains ( first order ) four degrees of freedom proposed a model using confirmatory factor analysis stata factor analysis, but conceptually different... Which items load on all factors on data comprising groups variables Principal-components factoring Total accounted... Test, and the demographic variables the initial model and other confirmatory factor analysis stata, must.

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