Choosing an appropriate real-life measure of effect size: the case of a continuous predictor and a binary outcome

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dc.creatorConroy, Ronan M.
dc.date2017-04-01T13:54:14Z
dc.date.accessioned2026-07-09T05:47:16Z
dc.descriptionA case study of data on age and pregnancy is used to point up some morals for practicing data analysts, including the superiority of regression over t tests, exploratory scatterplot smoothing as a key method of checking form of relationship, and the value of logistic regression followed by adjust as a way of getting at the numbers of most interest.
dc.identifierOther:st0021
dc.identifierdoi:10.22004/ag.econ.116011
dc.identifierhttps://ageconsearch.umn.edu/record/116011/files/sjart_st0021.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/116011
dc.identifier.urihttp://hdl.handle.net/123456789/568345
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/116011
dc.titleChoosing an appropriate real-life measure of effect size: the case of a continuous predictor and a binary outcome
dc.typeText

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