This is the last episode of the podcast, in which the hosts talk about ways to get involved in research. This includes writing grant proposals and submitting them, and getting a mentor. The hosts also discuss their own experiences with research, with one focusing on grant proposals and the other on manuscript writing. They encourage listeners to explore and learn more about research and funding sources. 1. Research is important for informing and improving medical practice. 2. Research can seem intimidating, but it is not as mysterious as it may seem. 3. Most research is flawed in some way, but it does not mean it is worthless. 4. Researchers may collaborate with statisticians who are experts in statistical analysis. 5. It is important to approach research with a healthy skepticism. 6. To get involved in research, reach out to professors, program directors, or the speakers for advice.

This episode of the podcast discusses the Kruskal-Wallis test, which is a non-parametric alternative to the one-way ANOVA test. It is used to compare multiple independent groups when the data does not meet the assumptions of the ANOVA. The test is appropriate for ordinal or non-normal data, and it compares the ranks of the data instead The podcast talks about before and after studies which is a type of pre-post design in quasi-experimental research. It is used when randomization is not possible or when there is no control group. The purpose is to measure the effects of an intervention or exposure on a population. The quality of the study can be assessed by looking at sample selection, confounders, regression to the mean, attrition bias, and outcome variables. The Mann-Whitney U test is a nonparametric test.

Meta-analysis is a research design that is a systematic review with formal statistics. It involves identifying a specific research question, assessing the quality of methods used, and synthesizing the results with statistical analysis. Meta-analysis provides increased power by combining multiple studies to show statistical significance. Possible biases include publication bias and outcome reporting bias. Meta-Analysis is a research method that combines and analyzes data from multiple studies. It is a powerful tool that can increase the statistical power of research and make important findings more apparent. However, like any research method, it has limitations and potential biases that should be considered. Negative predictive value and positive predictive value are two important measures used in diagnostic testing, and they are influenced by the prevalence of the disease being studied. Diagnostic tests are a good starting point for meta-analyses, and software developers.