As you sally forth into the land of structural equation modeling (SEM), you’ll come across terms like identification, and ideas like degrees of freedom (df) for a chi-square goodness of fit test. For many students, df is one of the more puzzling aspects of SEM. Sometimes it isn’t entirely clear where those degrees of freedom come from or why they have the values that they do. Continue reading
During a class today I was involved in an interesting discussion about the effective presentation of scientific findings. In particular, we chatted about the use (and abuse) of jargon and overuse of lofty or colorful language in research, and how overuse can undermine the message of your research. Continue reading
Like many others, I have historically used SPSS as my go-to data management program. Many of those with whom I work do the same, and with good reason. It’s flexible and fairly easy to use for basic data management tasks (and let’s be honest, most people are trained in SPSS during their initiation into data analysis in psychology). One life changing moment for many users of SPSS is the day that one realizes the utility of the syntax window vis a vis the point and click interface. This becomes more apparent during the data management phase than perhaps at any other point. This article assumes that you’re already past this point of no return.
During my undergraduate years I spent large segments of my working week learning SPSS. Much of it was trial and error (ok, mostly error), but in my trials I recall one consistent experience. An experience that is familiar to many other students, I’m sure.
The Model Fit Aggregator is a tool I designed for use with Mplus. It allows you to use the model fit information from any model you estimate via maximum likelihood estimation and plug it in (where instructed). The tool will aggregate the information from the raw output and spit out a single line of model fit statistics for you to paste into a manuscript, poster, talk, or other document. Continue reading
The Correlation Tabulator is a tool I designed for use with SPSS. It will require you to run a set of Pearson correlations in SPSS, paste the correlation table output into the tabulator (if you follow the instructions, of course). It will then take those results and compile them into an APA-style correlation table (coefficients reported to two decimal places, with asterisks indicating significance levels), which you can copy and paste into Word or a similar program.
The Regression Tabulator is an Excel-based tool developed for use with SPSS regression analysis output. It is designed to accommodate multiple regression with a maximum of 20 predictor variables (which you will need to define). If you paste your “Coefficients” table into the worksheet (with or without confidence intervals), it will convert your SPSS output into three APA-style tables for you to choose from. The first features complete information unstandardized coefficients (B, SE, t, p). The second and third are truncated tables (unstandardized and standardized, respectively) that include reports of the model coefficients and standard errors, with asterisks indicating significance levels.