Grimberg, Kutikov, and Cucchiara (2005) wondered whether gender biases were evident in referrals of children for poor growth. They believed that boys were more likely to be referred even when there was no problem-bad for boys because families of short boys might falsely view their height as a medical problem. They also believed that girls were less likely to be referred even when there was a problem-bad for girls because real problems might not be diagnosed and treated. They studied all new patients at The Children's Hospital of Philadelphia Diagnostic and Research Growth Center who were referred for potential problems related to short stature. Of the 182 boys who were referred, 27 had an underlying medical problem, 86 did not but were below norms for their age, and 69 were of normal height according to growth charts. Of the 96 girls who were referred, 39 had an underlying medical problem, 38 did not but were below norms for their age, and 19 were of normal height according to growth charts.
a. How many variables are there in this study? What are the levels of any variable you identified?
b. What hypothesis test would be used to analyze these data? Justify your answer.
c. Conduct the six steps of hypothesis testing for this example.
d. Calculate the appropriate measure of effect size. According to Cohen's conventions, what size effect is this?
e. Report the statistics as you would in a journal article.