Endgames Statistical Question

# Understanding P values

BMJ 2014; 349 (Published 11 July 2014) Cite this as: BMJ 2014;349:g4550
1. Philip Sedgwick, reader in medical statistics and medical education
1. 1Institute of Medical and Biomedical Education, St George’s, University of London, London, UK
1. p.sedgwick{at}sgul.ac.uk

Researchers investigated whether a low glycaemic index diet in pregnancy reduced the incidence of macrosomic (large for gestational age) infants in an at risk group. A randomised controlled trial study design was used. Participants were 800 women without diabetes, all in their second pregnancy, who had previously delivered an infant weighing more than 4000 g. The intervention consisted of a low glycaemic index diet from early pregnancy. The control treatment was no dietary intervention. The primary outcome was birth weight.1

Treatment groups were compared in mean birth weight using the independent samples t test. Hypothesis testing was two tailed, with a critical level of significance of 0.05 (5%). The mean birth weight in the intervention group was greater than in the control group, although the difference was not significant (4034 g (standard deviation 510) v 4006 (497); mean difference 28.6 g; 95% confidence interval −45.6 to 102.8; P=0.449). The researchers concluded that a low glycaemic index diet in pregnancy did not reduce the incidence of large for gestational age infants in a group at risk of fetal macrosomia.

Which of the following statements, if any, are true?

• a) Statistical hypothesis testing based on a critical level of significance is a dichotomous test

• b) The P value provides a direct statement about the direction of a difference between treatment groups in mean birth weight

• c) The P value is the probability that the alternative hypothesis was true