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Can you do factor analysis with binary variables?
If the model includes variables that are dichotomous or ordinal a factor analysis can be performed using a polychoric correlation matrix. Note that variables used with polychoric may be binary (0/1), ordinal, or continuous, but cannot be nominal (unordered categories).
Is confirmatory factor analysis SEM?
Confirmatory factor analysis (CFA) is the fundamental first step in running most types of SEM models. You want to do this first to verify the measurement quality of any and all latent constructs you’re using in your structural equation model. The term “regression” is an umbrella for numerous statistical methods.
Can you do SEM in Stata?
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). Stata’s new sem command fits SEMs.
Can you do SEM with categorical variables?
Absolutely, it can. The only issue is that the association measures between covariables are based on the covariance, or equivalently the linear regression slope coefficient. The adaptation that SEM can make to accommodate one or more categorical variables is to use robust standard errors, or bootstrap.
What kind of data can be subjected to factor analysis?
Unordered discrete data (i.e., “nominal”) can also factor analyzed, provided that what you observed has an underlying order.
Can I use factor analysis for categorical data?
The method of factor analysis is widely used as an exploratory tool to reduce the dimensionality of multivariate data. The fact that the standard model is strictly applicable only when the manifest variables are scaled is a serious limitation in social science where the variables are often categorical.
What is confirmatory factor analysis example?
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 one another, the researcher can create a model where the correlation between factor A and factor B is constrained to zero.
What is Nlcom in Stata?
nlcom is a postestimation command for use after sem, gsem, and other Stata estimation commands. nlcom computes point estimates, standard errors, z statistics, p-values, and confidence intervals for (possibly) nonlinear combinations of the estimated parameters.
Can you do structural equation modeling in Stata?
Stata: Data Analysis and Statistical Software Evaluate model fit. Compute indirect and total effects. Fit models by drawing a path diagram or using the straightforward command syntax. Learn about structural equation modeling (SEM).
What are the features of gsem in Stata?
If you are new to Stata and gsem, let us tell you that this is just one feature in a command that already has many features. gsem fits confirmatory factor models, seemingly unrelated models, SEMs, multilevel models, and all combinations thereof. It fits these models with outcomes that are continuous, binary, ordinal, count, and even survival.
What can you do with generalized structural equations in Stata?
Stata’s generalized structural equations model (SEM) command makes it easy to fit models on data comprising groups. With gsem’s features, you can perform a confirmatory factor analysis (CFA) and allow for differences between men and women by typing.
How is food diary data used in SEM?
We have simulated data from a nutrition study where people kept a food diary for two weeks. In this diary, each person tallied the number of servings of vegetables, fruits, grains, and candy they consumed that day. The data contain the two-week totals for each person in the study and a variable indicating whether the person was male or female.