The proportional odds (PO) assumption for ordinal regression analysis is often violated because it is strongly affected by sample size and the number of covariate patterns. To address this issue, the partial proportional odds (PPO) model and the generalized ordinal logit model were developed. However, these models are not typically used in research. One likely reason for this is the restriction of current statistical software packages: SPSS cannot perform the generalized ordinal logit model analysis and SAS requires data restructuring. This article illustrates the use of generalized ordinal logistic regression models to predict mathematics proficiency levels using Stata and compares the results from fitting PO models and generalized ordinal logistic regression models.

Researchers have a variety of options when choosing statistical software packages that can perform ordinal logistic regression analyses. However, statistical software, such as Stata, SAS, and SPSS, may use different techniques to estimate the parameters. The purpose of this article is to (1) illustrate the use of Stata, SAS and SPSS to fit proportional odds models using educational data; and (2) compare the features and results for fitting the proportional odds model using Stata OLOGIT, SAS PROC LOGISTIC (ascending and descending), and SPSS PLUM. The assumption of the proportional odds was tested, and the results of the fitted models were interpreted.

An increase in hepatic triglyceride (TG) contents usually results in non-alcoholic fatty liver disease (NAFLD) and related metabolic diseases. However, the mechanisms underlying perturbations of hepatic TG homeostasis remain largely unknown. Here, we showed that MicroRNA-124 was up-regulated in the livers of C57BL/6 mice fed a short-term high-fat-diet (HFD). Adenoviral overexpression of miR-124 in C57BL/6 mice led to accumulation of excessive triglycerides and up-regulation of lipogenic genes in the liver. We further identified tribbles homolog 3 (TRB3) as a direct target of miR-124. AKT signaling, which is negatively regulated by TRB3, was enhanced by miR-124 overexpression. Moreover, restoration of TRB3 expression markedly abolished the effect of miR-124 on hepatic TG metabolism. Therefore, our findings revealed that miR-124 played a role in mediating high-fat-diet induced TG accumulation in the liver.

The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal response variables when the proportional odds assumption is violated. This model seems to be underutilized. One major reason is the constraint of current statistical software packages. Statistical Package for the Social Sciences (SPSS) cannot perform the SL regression analysis, and SAS does not have the procedure developed to directly estimate the model. The purpose of this article was to illustrate the stereotype logistic (SL) regression model, and apply it to estimate mathematics proficiency level of high school students using Stata. In addition, it compared the results of fitting the PO model and the SL model. Data from the High School Longitudinal Study of 2009 (HSLS: 2009) (Ingels, et al., 2011) were used for the ordinal regression analyses.