Data analysis is performed in
stages, moving from simple to more complex. The first two steps are preparatory (data
cleaning and transformation) and to be completed in the first stage of analysis (cleaning
and transforming are ongoing processes during analysis as well). Once the data is
prepared, one-way analysis is used to begin to provide description at the individual or
more aggregate levels (e.g. district levels) and to show associations between one
INDEPENDENT variable and a DEPENDENT variable (outcome) of interest. For example, looking
at the mean weight for age z-scores (malnutrition outcome) by illness categories,
education categories, income groups, sex, ages, etc. One-way analysis is used any time
only one independent variable is used either for description of the population or for
analysis with any outcome variable. The primary uses of one-way analysis are listed below:
Contents:
Page 1
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Descriptive Analysis,
which provides overall averages and other descriptive statistics by groups, such as
geographical area. |
Page 2
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Targeting using
ranking by outcome indicators (for example, district by underweight prevalence). |
Page 3
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Exploring Associations
between an outcome variable and one independent variable (e.g. nutrition status by
education level). |