The last, and sometimes hardest, step for running any statistical model is writing up results.
As with most other steps, this one is a bit more complicated for structural equation models than it is for simpler models like linear regression.
Any good statistical report includes enough information that someone else could replicate your results with your data.
Predicting future outcomes, the next steps in a process, or the best choice(s) from an array of possibilities are all essential needs in many fields. The predictive model is used as a decision making tool in advertising and marketing, meteorology, economics, insurance, health care, engineering, and would probably be useful in your work too! (more…)
Most Multiple Imputation methods assume multivariate normality, so a common question is how to impute missing values from categorical variables.
Paul Allison, one of my favorite authors of statistical information for researchers, did a study that showed that the most common method actually gives worse results that listwise deletion. (Did I mention I’ve used it myself?) (more…)