For a logistic regression looking at the log-odds of obesity among 20 to 70 year olds, age was included as a predictor. Age was recorded into categories: 20-29, 30-39. 40-49, 50-59, and 60-70. Given it is an ordinal variable, the statistician acknowledged that age could be included in the logistic regression model as continuous or categorical. Suppose that the statistician used loglikelihood ratio test of nested models to examine whether age could be treated as continuous. First, what is the null hypothesis? O Age is not a predictor of obesity Age is appropriate as a continuous variable O Age is appropriate as a categorical variable O Age is a predictor of obesity
For a logistic regression looking at the log-odds of obesity among 20 to 70 year olds, age was included as a predictor. Age was recorded into categories: 20-29, 30-39. 40-49, 50-59, and 60-70. Given it is an ordinal variable, the statistician acknowledged that age could be included in the logistic regression model as continuous or categorical. Suppose that the statistician used loglikelihood ratio test of nested models to examine whether age could be treated as continuous. First, what is the null hypothesis? O Age is not a predictor of obesity Age is appropriate as a continuous variable O Age is appropriate as a categorical variable O Age is a predictor of obesity
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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Transcribed Image Text:For a logistic regression looking at the log-odds of obesity among 20 to 70 year olds, age was included as a predictor.
Age was recorded into categories: 20-29, 30-39. 40-49, 50-59, and 60-70. Given it is an ordinal variable, the
statistician acknowledged that age could be included in the logistic regression model as continuous or categorical.
Suppose that the statistician used loglikelihood ratio test of nested models to examine whether age could be treated as
continuous. First, what is the null hypothesis?
O Age is not a predictor of obesity
Age is appropriate as a continuous variable
O Age is appropriate as a categorical variable
O Age is a predictor of obesity
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