A standard logistic regression models the effect of age (20-29, 30-39, 40-49, 50-59, 60- 69) on experience of back pain (modeling yes vs. no). If age is included as a continuous covariate (with values 1, 2, 3, etc., as scores) and the regression parameter associated with age is estimated to be 0.21 with standard error of 0.08, a likelihood-ratio hypothesis test is performed to see whether age could be considered as continuous (as assumed above) or categorical. Having proven nesting, how many degrees of freedom would be associated with sampling distribution of the likelihood ratio test statistic?
A standard logistic regression models the effect of age (20-29, 30-39, 40-49, 50-59, 60- 69) on experience of back pain (modeling yes vs. no). If age is included as a continuous covariate (with values 1, 2, 3, etc., as scores) and the regression parameter associated with age is estimated to be 0.21 with standard error of 0.08, a likelihood-ratio hypothesis test is performed to see whether age could be considered as continuous (as assumed above) or categorical. Having proven nesting, how many degrees of freedom would be associated with sampling distribution of the likelihood ratio test statistic?
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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A standard logistic regression models the effect of age (20-29, 30-39, 40-49, 50-59, 60-
69) on experience of back pain (modeling yes vs. no). If age is included as a continuous covariate (with values 1, 2, 3, etc., as scores) and the regression parameter associated with age is estimated to be 0.21 with standard error of 0.08, a likelihood-ratio hypothesis test is performed to see whether age could be considered as continuous (as assumed above) or categorical. Having proven nesting, how many degrees of freedom would be associated with sampling distribution of the likelihood ratio test statistic?
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