Using lme4 to predict probability of appendicitis
On Mon, 2011-01-31 at 17:49 +0000, Dale.W.Steele at gmail.com wrote:
Apologies for the repeat post ... (new subject)
...but you failed to start a new message (and thus get a new message-id) so most sensible mailers still think your email belongs to the thread entitled "Logistic regression with spatial autocorrelation structure". Is it that difficult to start a *new* message and paste in the email address for the list, rather than click reply? G
Dear mixed-modeling experts, I'm interested in modeling the probability of appendicitis in patients with abdominal pain. The R binary data file 'http://www.ped-em.org/appy.rda' contains the following variables from a pilot study of 138 children with abdominal pain. 'dx' eventual diagnosis: 0=no appendicitis, 1=appendicitis 'gender' Male/Female 'wbc' total white blood cell count 'priorprob' Clinical predicted probability of appendicitis 'doc' doctor who assigned 'priorprob' After taking a history and performing a physical examination, the ER doctor was asked to make a vertical mark on a 100 mm horizontal line to represent her estimate of the (percent) probability that the patient had appendicitis. My initial thought was to fit a multiple logistic regression model: m1 <- glm(dx ~ gender + priorprob + wbc + doc, family=binomial, data=appy) However, it seems likely that each doctor interpreted the probability scale differently. The 23 doctors evaluated from 1 to 17 patients each. I'm not primarily interest in predictions by a specific clinician. Thus, it seems to make sense to fit a generalized linear mixed model. At this point I get muddled. Have I correctly specified a random intercept model (m2) and a random intercept/random slope model (m3)? Are there other sensible models? library(lme4) m2 <- glmer(dx ~ priorprob + gender + wbc + (1 | doc), family=binomial, data=appy) m3 <- glmer(dx ~ priorprob + gender + wbc + (priorprob | doc), family=binomial, data=appy) My ultimate goal is to estimate the probability of appendicitis (and a prediction interval), given a specific 'gender', 'wbc' and 'priorprob' assigned by a doctor with similar diagnostic ability to those who participated in our pilot study. I'm stuck on how to code this prediction. Thanks. Dale Dale Steele, MD Pediatric Emergency Medicine Hasbro Childrens' Hospital Providence, RI [[alternative HTML version deleted]]
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