Analysis of Covariance ANCOVA

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Presentation transcript:

Analysis of Covariance ANCOVA Lecture 15 Analysis of Covariance ANCOVA

What is ANCOVA? This refers to the situation when the explanatory variables are both categorical and quantitative. The response variable however is always quantitative.

Recall: We have data on 78 seventh grade high school students in a rural Midwestern school. The researcher was interested in the relationship between “self-concept” (as measured by a test designed by himself) and the performance of the student. The data for each student include: GPA (not specified the period) (y, response variable) OBS – an observation number (if an observation number misses it means that the corresponding student dropped the study) IQ – score at a standard IQ test (IQ, explanatory variable) Gender – self explanatory Concept – score at the self designed test (CONCEPT, explanatory variable) We analyzed this data with multiple regression. We did not look at the gender variable. We will correct this oversight.

ANCOVA – the model. The model fitted for the example shown is: Where: - an overall constant - the effect due to categorical var (gender) - the regression coefficients - the explanatory variables - the response variable - the errors assumed to be normal and constant variance

The model is quite complex to describe in the case of two or more categorical variables but the software gives you answers regardless. The important issue is to be able to understand the answers and to make sure that the hypotheses under which these numbers were obtained are satisfied.