Mixture models are measurement models that use observed variables as indicators of one or more nominal latent variables (i.e. categorical variables). One way to think about mixture models that one…
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Search Results for: what stat should i use
Mplus Class Notes Structural Equation Models
In previous sections we have shown how to estimate two types of measurement models, confirmatory factor models, and mixture models (e.g., latent class analysis). We have also shown how to…
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Frequently Asked Questions
What Statistical Analysis Should I Use? General FAQs R FAQs SAS FAQs SPSS FAQs Stata FAQs Mplus FAQs SUDAAN FAQs
FAQ: What are pseudo R-squareds?
FAQ: What are pseudo R-squareds? As a starting point, recall that a non-pseudo R-squared is a statistic generated in ordinary least squares (OLS) regression that is often used as…
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FAQ What is complete or quasi-complete separation in logistic regression and how can I deal with them?
Occasionally when running a logistic or a multinomial logistic regression we would run into the problem of so-called complete separation or quasi-complete separation. On this page, we will discuss what…
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FAQ What is complete or quasi-complete separation in logistic/probit regression and how do we deal with them?
Occasionally when running a logistic/probit regression we run into the problem of so-called complete separation or quasi-complete separation. On this page, we will discuss what complete or quasi-complete separation is…
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FAQ: How are the likelihood ratio, Wald, and Lagrange multiplier (score) tests different and/or similar?
Purpose: This page introduces the concepts of the a) likelihood ratio test, b) Wald test, and c) score test. To see how the likelihood ratio test and Wald test are…
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FAQ: Why are R2 and F so large for models without a constant?
When I run my OLS regression model with a constant I get an R2 of about 0.35 and an F-ratio around 100. When I run the same model without a…
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FAQ: What is regression through the origin?
FAQ: What is regression through the origin? Regression through the origin is a technique used in some disciplines when theory suggests that the regression line must run through the origin,…
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FAQ What is complete or quasi-complete separation in logistic regression and what are some strategies to deal with the issue?
Occasionally when running a logistic regression we would run into the problem of so-called complete separation or quasi-complete separation. On this page, we will discuss what complete or quasi-complete separation…
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