ACPM Podcast

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-expe...

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...

Listen to the discussion about sensitivity and specificity in diagnostic tests. Sensitivity is the ability of a test to correctly identify people who have the disease, while specificity is the ability of a test to correctly identify people who do not have the disease. A high sensitivity rules in the disease, while a high specificity rules out the disease. It is possible to conduct systematic reviews and meta-analyses on the sensiti...

This episode discusses qualitative research, which is a form of research that involves collecting and analyzing non-numerical data, such as interviews and observations. Qualitative research can provide insights and understanding of people's experiences and perceptions, and can be used to inform quantitative research. Its strengths include flexibility and the generation of meaningful insights, while its disadvantages include be...

This podcast episode talks about randomized controlled trials (RCTs) and how they are used in research to evaluate the effectiveness of interventions. The hosts also discuss the importance of adjusting for confounding in RCTs and how multiple regression can be used to do this in the analysis phase. They also touch on the assumptions of multiple regression, such as linearity, independence, normality, and equal variance. This episode...

Today, we talked about the importance of understanding which statistical test to use for your research based on your variables. Anova and the student's t test both test for means, but Anova is better for more than two populations and categories, while the student's t test is better for dichotomous or binary variables. It all depends on your research question and variables. Cross-sectional studies are a type of observation...

Researchers have conducted a new study using a statistical method called "factor analysis" to analyze and interpret large amounts of data. This method can help identify patterns and relationships within data. Stay tuned for more This week's episode of the Podiatry Research Podcast discussed the case control study design. This type of study starts with a group of participants with a specific outcome (cases) and a grou...

Our fourth podcast episode talks about pros and cons of research. The hosts discuss simple linear regression and its importance in research. They explain the assumptions that need to be met in order to use this statistical method, including independence, normality, and equal variance. They also mention the information that simple linear regression can provide, such as P-value, 95% confidence interval, root mean squared error, and b...

 Logistic regression is a statistical method used to predict a binary outcome (yes or no, true or false). It calculates the odds ratio, which is the probability of the outcome occurring. This method does not require the same assumptions as linear regression. It can be used in research studies where the outcome is categorical rather than numerical, and can consider multiple variables and adjust for confounding factors. A study on pr...

 Statistical tests such as the Chi-Square test and Fisher's Exact test are commonly used in research to determine if there is a significant association or difference between two variables. They can be used to compare groups, survey populations, assess response bias, and more. Negative studies, where the p-value is not significant, are also important and should still be published. A case series is a detailed report of a group o...

 The episode discusses the history of statistics and its importance in research, especially in the medical field. It also explains the different types of statistics (frequentist and Bayesian) and the importance of being able to critically appraise research papers and choose the appropriate research design and statistical analysis. The episode ends by encouraging researchers to tune in for future episodes that will cover different r...