I was talking to a colleague about modeling nominal outcomes in STAN, and wrote up this example. Just put it here in case it’s helpful for anyone (probably myself in the future).

The current study introduces the Bayesian region of measurement equivalence (ROME) method for visualizing and quantifying such biases. ROME estimates the most probable magnitudes of test bias for individuals with different construct scores and compares it to a predefined region of tolerable bias levels.

Measurement invariance---that a test measures the same construct in the same way across subgroups---needs to hold for subgroup comparisons to be meaningful. There has been tremendous growth in measurement invariance research in the past decade. …

library(SimDesign) library(cmdstanr) [Update: Use parallel computing with two cores.]
Adapted from https://cran.r-project.org/web/packages/SimDesign/vignettes/SimDesign-intro.html
See https://mc-stan.org/cmdstanr/articles/cmdstanr.html for using cmdstanr
Design <- createDesign(sample_size = c(30, 60, 120, 240), distribution = c('norm', 'chi')) Design ## # A tibble: 8 × 2 ## sample_size distribution ## <dbl> <chr> ## 1 30 norm ## 2 60 norm ## 3 120 norm ## 4 240 norm ## 5 30 chi ## 6 60 chi ## 7 120 chi ## 8 240 chi Generate <- function(condition, fixed_objects = NULL) { N <- condition$sample_size dist <- condition$distribution if(dist == 'norm'){ dat <- rnorm(N, mean = 3) } else if(dist == 'chi'){ dat <- rchisq(N, df = 3) } dat } Define Bayes estimator of the mean with STAN

Complexity of MLM Information Criteria Example Selecting Fixed Effects How to Choose Between AIC and BIC? Including Lv-2 Predictors Workflow Regularization Bibliography In social sciences, many times we use statistical methods to answer well-defined research questions that are derived from some theory or previous research.

Quasi-Bayesian/Monte Carlo CI With the mediation Package
Analytical Approaches for CI With the RMediation Package
Distribution of Product of Coefficients
Asymptotic Normal CI
Case Bootstrap
Bootstrap CI
Fully Bayesian Approach With rstan
Posterior (Credible) Intervals
Summary Table of Different CIs:
Bibliography
The data are from the mediation package, which are simulated data with the source of the Education Longitudinal Study of 2002.

© 2022 Hok Chio (Mark) Lai

Powered by the Academic theme for Hugo.