The random variables can take either discrete or continuous numerical values 3, 4, 5. These types of questions are commonly addressed by correlations and the related hypothesis testing.Ĭorrelation is a monotonic (often linear) association between two random variables X and Y. Moreover, researchers are often interested in another type of bivariate relationship - between two numerical measurements, such as how a patient’s age is related to the titer of Covid-19 antibody or how a patient’s BMI is related to the severity of Covid-19 symptoms, etc. This Table-1 is thus very informative and often essential for a medical research paper 1, 2. The statistical hypothesis tests from which the p-values are computed can be Student’s t-test, Wilcoxon Rank-sum test, or Chi-squared test (or Fisher’s exact test), etc. Depending on the types of characteristics, the strength of a bivariate association can be mean difference, odds ratio, or percent difference, etc. This table is often a cross-table stratified by study groups, for example, medical treatments and a range of bivariate associations between each of the patients’ characteristics and the stratifying group can be incorporated into this table as well. In medical research, we often provide a single table called Table-1 to summarize the characteristics of our study subjects, such as patients’ age, sex and lab test results. ![]() It has been fully tested in different SAS interfaces and is incorporated with the SAS ODS system. This SAS macro is simple and easy to use, and it provides a one-stop, powerful tool for all types of correlation studies between two numerical variables. To assist in the interpretation of results, it can also optionally produce footnotes and publication-quality figures to visualize the relationship between variables. This document contains the summary statistics of numerical variables, an appropriate correlation coefficient between two numerical variables with its confidence interval, and the p-value from hypothesis testing for association. ![]() To supplement these Table-1s, there is a SAS macro that produces a publication-ready document that reports in a single table. However, these cross tables cannot provide the bivariate associations between two numerical variables. There are many user-written SAS macros dedicated to producing such a Table-1 with minimal effort. ![]() This single table provides the appropriate summary statistics for all numerical and categorical variables assessed in the study, as well as their bivariate associations with the categorical variable that they are stratified by. Table-1 is an informative cross table that consists of a set of numerical and categorical variables in rows stratified by a categorical variable in the columns. In academic and particularly medical research, the essential first set of results are often summarized in a table called Table-1. Bowen (Charles) Zheng, Episcopal High School Abstract
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