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Three-Way Repeated Measures ANOVA The three-way repeated measures ANOVA is a robust statistical test used in experimental psychology and other scientific fields. The three-way repeated measures ANOVA enables researchers to explore complex interactions among three within-subject factors on a continuous outcome, thus extending the capabilities of the two-way repeated measures ANOVA by incorporating an additional […]

Independent-Samples T-Test The independent-samples t-test is used to determine if a difference exists between the means of two independent groups on a continuous dependent variable. More specifically, it will let you determine whether the difference between these two groups is statistically significant. This test is also known by a number of different names, including the

Multiple Regression A multiple regression is used to predict a continuous dependent variable based on multiple independent variables. As such, it extends simple linear regression, which is used when you have only one continuous independent variable. Multiple regression also allows you to determine the overall fit (variance explained) of the model and the relative contribution of

Regression Analysis A simple linear regression analysis is a statistical method that helps to predict the value of a dependent variable based on the value of an independent variable. It assesses the linear relationship between two continuous variables and provides insights into the relationship’s direction, magnitude, and statistical significance. For instance, you can use simple

Correlation Analysis The correlation analysis is used to determine the strength and direction of a linear relationship between two continuous variables. More specifically, the test generates a coefficient called the Pearson correlation coefficient, denoted as r (i.e., the italic lowercase letter r), and it is this coefficient that measures the strength and direction of a linear

Paired-Samples T-Test The paired-samples t-test serves the purpose of assessing whether the mean discrepancy between interconnected observations is statistically significant. These observations may involve the same individuals evaluated at two distinct time points or be subjected to two conditions concerning the same dependent variable. Alternatively, you might have two sets of participants matched based on

Chi-Square Test The chi-square test can be used to test a variety of sizes of contingency tables, as well as more than one type of null and alternative hypotheses. This guide focuses on contingency tables that are greater than 2 x 2, which are often referred to as r x c contingency tables, and tests whether

Kaplan-Meier Analysis The Kaplan-Meier analysis (Kaplan & Meier, 1958) (also known as the “product-limit method”) is a nonparametric method used to estimate the probability of survival past given time points (i.e., it calculates a survival distribution). Furthermore, the survival distributions of two or more groups of a between-subjects factor can be compared for equality. For