Compares the theoretical bases of ANOVA, ANCOVA, MANOVA and MANCOVA and examines their utilization in behavioural science.
Written in 2002; 4,742 words; 17 sources; APA; $ 121.95
Paper Summary:
In the realm of behavioral science, researchers try to understand the psychological workings of a population by examining the traits, or variables, of a smaller sample. Statistical analyses on the data collected from samples are used in order to understand how observed behavioral phenomena generalize to a broader population. The paper shows that the main goal of this kind of research is to define what is average or typical of a group in regards to a certain characteristic or condition. A systematic comparison of the average tendencies of two or more groups yields a more accurate evaluation of group similarities and differences than does an informal examination of the data. This paper discusses and compares the four methods of testing: Analysis of variance (ANOVA), Analysis of Covariance (ANCOVA) and their multivariate equivalence (MANOVA and MANCOVA).
From the Paper:
"Overall, MANOVA is utilized when a researcher desires an ANOVA-like analysis for more than one dependent variable. The main purpose of MANOVA is to test whether mean differences among the independent variable on a combination of dependent variables are due to chance or a real effect. This is achieved by creating a single dependent measure from a combination of all dependent measures that maximizes the between group differences. Including more than one dependent measure improves the researcher's chance of discovering what can change between different treatments or measures that more clearly defines the group."
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