1. CATEGORICAL DATA ANALYSIS Eni Sumarminingsih, S.Si, MM

2. CATEGORICAL RESPONSE DATA A categorical variable is one for which the measurement scale consists of set of categories Ex :  political philosophy : liberal, moderate, conservative  Smoking status : never smoked, former smoker, current smoker  Recovery from an operation : completely recovered, recovered, nearly recovered, only somewhat recovered, not at all recovered

3. Response/Explanatory Distinction Most statistical analyses distinguish between response (or dependent) variables and explanatory (or independent) variables This course is concerned with the analysis of categorical response variables. For some methods, the explanatory variables must also be categorical ; for others, they can be continous or categorical

4. Measurement Scala Distinction Nominal : categorical variable for which levels do not have a natural ordering. Ex: religious affiliation, mode of transportation, choice of residence, race, gender, and marital status. Ordinal : categorical variable for which do have ordered levels. Ex : social class, size of automobile Interval : variables that have numerical distance between any two levels for the scale. Ex : blood presure level, income

5. Continous/Discrete Distinction Variables are classified as continous or discrete, according to the number of value they can attain

6. Quantitative/Qualitative Disticntion Qualitative : distinct levels differ in quality, not in quantity (nominal variable) Quantitative : disticnt levels have differing amounts of the characteristic of interest (interval variable)

7. What we learn in this course  Descriptive and inferential methods for bivariate categorical response Basic measures of association  Develops the basic of model building Logit model : used with binomial or multinomial response Loglinear model : used with Poisson response

8. Refference  Categorical Data Analysis Alan Agresti University of Florida Gainesville, Florida John Wiley & Son  Source from Internet