Questions tagged [confirmatory-factor]

Confirmatory Factor Analysis (CFA) is a set of multivariate techniques aimed at validating the relations between the observed variables, or indicators, and underlying latent variables, or factors, and is typically used to describe the underlying structure of psychological scales and other social science measurements.

Filter by
Sorted by
Tagged with
0
votes
0answers
14 views

Comparing two CFA models in AMOS (few items per factor)

I am trying to test in AMOS the discriminant validity of a 3-item measure (items "1, 2 and 3" against a 1-item measure "item Z" (both are Likert scale questionnaire instruments), by comparing whether ...
0
votes
2answers
26 views

Can you do CFA with non-survey data?

I have a dataset with countries as observations and 33 country-level continuous variables. The information accompanying the dataset groups the 33 variables into 6 different 'categories', however I am ...
0
votes
1answer
16 views

Are these latent variables too highly correlated in this Structural Equation Model?

this is my first SEM I've done so I'm still getting my head around many of the concepts. So I think I've created a hierarchical model of IQ (generaliq), with the latent variables: verbal_letter, ...
1
vote
2answers
19 views

CFA markers and latent variable's variance [closed]

In Confirmatory Factor Analysis (CFA) we set a marker (regression weight = 1) to a randomly or not randomly chosen observed variable. I was wondering under which conditions or in which situation you ...
3
votes
2answers
138 views

Non-significant result in CFA model

I've fitted a one-factor model to data originating from a unidimensional 8-item scale; sample size is 400. Because the scale uses a Likert response format, and data does not follow a multivariate ...
1
vote
0answers
12 views

Obtain standardized factor scores for latent variables after CFA - Lavaan package in R

I want to predict the factor scores of latent variables from CFA, and use them as independent variables in another model (not SEM). Because the latent variables don't have a measurement unit, I want ...
0
votes
1answer
10 views

How to calculate composite score with a 2-factor scale

Suppose I have a scale with four items meant to measure, say, happiness. I ran a confirmatory factor analysis and the model fits well with two factors and let's say that the two factors are 1) ...
0
votes
0answers
22 views

What does it mean if EFA shows worse fit than conceptual CFA?

I'm in the middle of developing a psychometric scale and running a few factor analyses here and there. I already have a theory in mind and the scale was developed with 4 factors. I ran a confirmatory ...
0
votes
0answers
48 views

How to interpret output of measurement invariance analysis

I try to test the measure invariance of a scale (with a 1-factor-structure) across two groups (N_1 = 645; N_2 = 127) and have problems with the application as well as the interpretation. I'm sure they'...
0
votes
0answers
16 views

Best choice of estimators in a CFA analysis without full dataset?

My team and I are working on an assignment that provided: A model to be tested, consisting of 2 Factors explaining 6 variables; $F1$ would be explained by $X1, X2$ and $X3$, while $F2$ would be ...
0
votes
1answer
25 views

Normality test without knowing a sample's mean

I've been searching for a way to approach my problem. This is a scenario from a Multivariate Statistics Assignment on Confirmatory Factor Analysis. We've been given only a correlation matrix on 6 ...
0
votes
0answers
9 views

Multiple factor analysis: Getting more number of factors than the number of dimensions/ features

I am trying to apply multiple factor analysis on a survey data, which has all sorts of features - numerical, categorical and ordinal. In total, there are 109 features. Now, when I did multiple factor ...
0
votes
0answers
9 views

Partial least square

In the context of confirmatory factor analysis, structural equation modeling, & predictor space dimension reduction. PLS is a supervised dimension reduction procedure, since it summarize the ...
0
votes
1answer
42 views

Minimum value for Squared multiple correlations between items and factors

When building a CFA model, each of item that form a latent variable has its own squared multiple correlation coefficient or reability. Is there a minimum value for squared multiple correlations (R^2)? ...
0
votes
1answer
27 views

Reverse coding items: missing data + factor analysis

I have a data set which includes a number of variables which need to be reverse coded. I have already completed my missing data analysis, however did not reverse code the items prior to replacing the ...
0
votes
1answer
38 views

Measurement invariance using 3 items

I want to examine measurement invariance across two nationalities for a construct measured with 3 items. First one is supposed to examine the configural fit before examining more restrictive models. ...
1
vote
1answer
37 views

CFA: scaling of measured variables/indicators

I'm running a latent variable analysis with: 166 observations 21 continuous variables using the R package lavaan A simple run of ...
0
votes
0answers
15 views

Exploratory Factor Analysis and Confirmatory Analysis

I am seeking to apply these methods to psychological questionnaire data. I have read up on the basics but I am curious - and this is not limited to just ECA/CFA, but what is the best method to look up ...
0
votes
0answers
15 views

Calculating a single Factor value against a table of variables

Ok here's a fun one... We have to calculate a given referee's strength rating/appropriateness for refereeing a given game. The number we come up with has to be something meaningful, so it should be ...
0
votes
0answers
6 views

Multigroup Factor Analysis - Scale Validation

I have a questionnaire which comprises of several factors or constructs. I gave the question to two groups and have received my answers back I wanted to use MGFA to determine if my questionnaire was ...
2
votes
1answer
40 views

Do I estimate factor loadings in a confirmatory factor anlysis (CFA) aimed at verifying an exploratory factor analysis (EFA)?

I decided to use a questionnaire published by another researcher (paper and supplementary here). In the article they perform an EFA, find two factors, and report the resulting factor loadings (...
0
votes
1answer
31 views

Does a poorly fitting CFA preclude SEM?

Trying to help someone with a Masters dissertation. I've run CFA in Jamovi on her questionnaire responses based on the assumed item/factor relationships. I don't really understand the various ...
0
votes
1answer
31 views

SEM: Comparing models when removing paths

I'm developing an SEM model for a study I've recently run. Essentially, I have 6 factors that are shown from previous research to predict one's performance in a specific task. My data is the ...
0
votes
1answer
14 views

What are the most common optimization algorithms for confirmatory factor analysis?

For confirmatory factor analysis, as I understand it, we have the following set up: Source: Sacha Epskamp’s lecture notes I then read that some authors have tried the following approaches Source: ...
0
votes
2answers
14 views

Collapsed Categories - Interval or Ordinal Scale

Is it appropriate to treat the following indicator as having an interval scale: "In the last two weeks, how many times have you been late for school: 1. Never (62% of respondents) 2. Once or twice (15%...
0
votes
0answers
15 views

Is there a Latent Class Analysis analog for Confirmatory Factor Analysis?

I am looking to do modeling similar to Confirmatory Factor Analysis with path diagrams, correlations, etc. but all my variables are categorical. I read that, when dealing with continuous variables, it ...
1
vote
3answers
319 views

lavaan WLSMV estimator: are results reliable when number of observations is too small to compute Gamma?

I run CFA (confirmatory factor analysis) with WLSMV estimator (since my data are ordinal) in lavaan and I get the following warning message: ...
0
votes
0answers
14 views

Should a factor analysis (for construct validity) be performed in a section of a test that is meant to measure knowledge in a specific subject?

As a part of a study, a survey to measure the impact of an environmental education project is being developed, and to do so, factor analysis and principal component analysis are being performed for ...
0
votes
0answers
63 views

factor scores from CFA in lavaan

I have the covariance matrix and an already fitted lavaan object (and/or model) using the cov matrix. But, I do not have the raw data. Is there a way I can calculate the factor scores?
0
votes
0answers
13 views

Resampling or simulating orginal data to assess validity of experimental measure

I would like to conduct combination of EFA and CFA to assess if the measure I've designed to evaluate results of an experiment fits into proposed theoretical model or not. My theoretical model ...
0
votes
0answers
25 views

How to estimate a measurement model (CFA) with both latent and observed variables affecting measurements in lavaan?

I'd like to estimate a CFA model where measures are determined by both latent variables and other observed variables. I can do this by creating place-holding latent variables for the observed ...
3
votes
1answer
154 views

How can Factor Analysis be used to remove questions from a survey?

Suppose I have a psychological questionnaire asking 30 questions about a person's mental health (on a Likert-scale 1-7). These 30 questions fall into 7 separate, but correlated categories. The ...
2
votes
1answer
43 views

Is there a point to using EFA for scale validation when you can always fit a second-order CFA?

I have been trying to understand the use of Exploratory Factor Analysis for the purpose of scale validation. Say you have developed a scale to measure construct X, which is supposed to be one unified ...
0
votes
1answer
63 views

how can I perform confirmatory factor analysis when covariance matrix contains missing values?

I have dataset of test items which were administered in blocks. As a result, not all students answered each test item and there are some pairs of items for which no observations are shared, ...
2
votes
2answers
217 views

In CFA, does it matter which factor loading is set to 1?

I'd been previously taught that, aside from the fact that fixing a loading to 1 means you won't get a significance test on that loading, it was totally arbitrary which loading got fixed to 1. However,...
1
vote
0answers
70 views

Do I report the pvalue of the standardized or unstandardized factor loading in CFA/SEM?

Using lavaan, for a simple CFA or SEM with measurement tools, you can use parameterEstimates(fit, standardized=TRUE) to get the standardized factor loadings for the ...
2
votes
0answers
18 views

$H_0$ and $H_1$ of $\chi^2$ test in confirmatory factor analysis

I am struggling to find a good text on confirmatory factor analysis (CFA) (an old thread on the topic has little to offer) and so have some basic questions on CFA. What exactly are the null and the ...
1
vote
1answer
30 views

EFA over time where changes in the factors are of interest

I am asking to find out if an idea that popped into my head is a real thing or just silly. EFA often presumes the data are static. I know there are forms of EFA that take time into account, but I ...
1
vote
1answer
156 views

Checking error covariances between indicator variables in sem/cfa

I'm learning SEM/CFA, and am currently following Beaujean's (2014) book on using lavaan. In the chapter where he talked about CFA and the number of indicator variables to have to ensure the model ...
0
votes
0answers
29 views

Should AVE and CR be estimated with EFA?

I have conducted an exploratory factor analysis with maximum likelihood (MLFA) and oblique rotation (Promax). I am now trying to estimate validity and reliability (AVE, CR, etc.) moving beyond ...
0
votes
0answers
14 views

Why do I get an error with this data using principal axis factoring but not minimal residual factoring?

I am using n_factors() from the "psycho" package in R to figure out the number of factors for a set of data. When I use prinicipal axis factoring I get the following error: ...
0
votes
0answers
16 views

My question is about factor covariance in CFA

I did a CFA for a scale with 4 factors. the model is fitted( RMSEA, CFI, GFI...) But some factors covariance is very low and also χ2/df is significant.Is it a problem? Thanks
0
votes
0answers
43 views

Linear Regression Perfectly Predicts Latent Variables

I'm having trouble understanding the relationship between the latent variables produced by the CFA function in R's Lavaan package, and linear regression. I have used one of Lavaan's built-in data ...
0
votes
1answer
101 views

How do I specify a lavaan sem model with more than one single-indicator factor?

I am trying to specify a lavaan CFA that has some factors with three or more indicators, one factor with two indicators, and two factors with one indicator. For the single indicator factors, I tried ...
0
votes
0answers
59 views

How to Determine Appropriate Values for Correlated Uniqueness in SEM Simulation?

I am trying to run a simulation of power/bias for a particular SEM, in which a number of correlated uniquenesses will need to be specified. I know how to determine the appropriate values of the ...
0
votes
0answers
108 views

Acceptable CFI but poor TLI

I'm working on a path analysis using lavaan in R. Here is my model fit result: Chi square: >.05 Confirmatory Fit Index (CFI): 0.94 Tucker Lewis Index (TLI): 0.86 Root Mean Square Error of ...
0
votes
0answers
73 views

Lavaan LavPredict when samples have 0 variance

I am using Lavaan to perform a Confirmatory Factor Analysis on a dataset of 10,000 League of Legends games. The features of the dataset are certain variables of the games like kills, deaths, gold ...
0
votes
1answer
143 views

Evaluating measurement invariance with lavaan and ordered data

I am running a measurement invariance in lavaan in R. I am comparing a measure of sociocultural appearance pressures across White and Black women. Because this is a 5-point scale, I am treating the ...
1
vote
2answers
150 views

AIC and BIC come out as NA when running CFA in R

Does anyone have ideas why when running a CFA in R I'm getting most of my fit statistics to calculate, but AIC and BIC are both NA? I load lavaan, SEMplot, SEMtools, and haven; load the file (have ...
0
votes
0answers
58 views

Reasons for markedly different results using MLR vs. WLSMV in CFA?

A scale I examined has a 6-point likert scale and detailed anchor points. In addition, the items are distributed skew. I did a CFA with MLR as well as with WLSMV. With WLSMV as estimator, the scale ...