Assessment, Statistics, and Research

  A post hoc test is a statistical test used to determine if a pair of values are significantly different from each other after the primary analysis has been completed. Post Hoc Tests / Suttong.com AI Infographic The term post hoc is a Latin phrase meaning "after the event." A common use of post hoc tests is the comparison of group means following an F -test in an ANOVA has revealed significant differences among the groups. The reason to test for differences after an overall test like ANOVA is to reduce the risk of finding a significant difference by chance. That is, if researchers perform a large number of tests on a sample, they may find one or more tests yield significant results by chance. There are many post hoc tests. Following are some examples of tests that compare the means of two groups. Bonferroni Test This is a popular test. By dividing the significance level by the number of comparisons, the risk of finding a significant difference by chance is reduced. This proc...

  Covariate A variable that is correlated with a dependent variable in a research study. When a covariate is identified and measured, the value of the dependent variable can be adjusted for the contribution of the covariate during data analysis (Sutton, 2021, January 14). Example: If researchers collect information on the variable age in a study about forgiveness and if age is related to forgiveness, then age can be treated as a covariate to identify how people scored on a forgiveness survey after the scores have been adjusted for age. The word adjusted is a keyword to look for in reading research that includes a covariate. Learn more --> Procedures that include covariates are ANCOVA and MANCOVA . Cite this post. Sutton, G. W. (2021, January 14). Covariate. Statistics .  https://statistics.suttong.com/2021/01/covariate.html Please subscribe to this blog for updated statistics and measures. Applied Statistics Concepts for Counselors on  AMAZON  or  GOOGLE Cre...

  MANCOVA (Multivariate Analysis of Covariance). A statistical procedure for analyzing results when there are one or more independent variables , two or more dependent variables , and one or more covariates . Basic components of MANCOVA Independent or grouping Variable = 1 or more Dependent or criterion Variable = 2 or more Covariates = 1 or more Overall tests are used to determine significant effects or differences among the grouping variables. An F test indicates significance overall and for specific effects or relationships. A commonly reported measure of effect size is eta squared. A p value reveals the probability of a significant relationship-- one that is not due to chance factors. Applied Statistics Concepts for Counselors on  AMAZON  or  GOOGLE Creating Surveys on AMAZON    or   GOOGLE  Worldwide Links to Connections   Checkout My Website     www.suttong.com    See my Books      AMA...

ANCOVA: Summary and Key Features Geoffrey W. Sutton, PhD at suttong.com Part 1 of 2 Analysis of Covariance (ANCOVA) is an extension of ANOVA that allows researchers to compare group means after statistically adjusting for one or more additional variables, called covariates (CVs). Covariates are not the main focus of the study but are included because they are systematically related to the dependent variable (DV) and may influence group differences (Sutton, 2020, 2021). Reference: Sutton, G. W. (2021). Creating surveys: Second Edition: How to create and administer surveys, evaluate workshops & seminars, interpret and present results. Sunflower. ISBN-13:  9798712780327   [I earn income from book sales.] ***** The central idea is adjustment: Before comparing groups, ANCOVA adjusts DV scores based on the covariate, producing adjusted means that better reflect the true effect of the independent variable (IV). Why Use ANCOVA? To reduce error variance and increase statisti...