Assessment of the sample size adequacy
depressive, stunting
REGRESSION
Two power calculations were performed considering a range of possible type-I error rates defined according to the Benjamini–Hochberg procedure. The first power post-hoc calculation was for the latent factor model, investigating household demographic and socioeconomic characteristics in relation to infants’ physical growth through postpartum depressive symptom and breastfeeding status. Based on a Root Mean Standard Error (RMSE) of 0.05, a type I error rate in the range of 0.1–0.05% (0.0005 < α < 0.001), a sample size of 313 to 330 participants is sufficient to guarantee a type-II error rate below 10% (1 − β > 0.8) in a structural equation model with more than 100 degrees of freedom. The second post-hoc power calculation performed was for the binomial function, estimating the risk of stunting and underweight. Given a type I error rate in the range of 0.1–0.05% and a risk ratio (RR) estimate greater than 1.5, a sample size of 350–400 participants would confirm a type-II error or a false negative rate below 10% (statistical power 1 − β ≥ 0.9). The semPower and the pwr packages of the R software were used for the power calculation of the latent factor model and binomial regression, respectively.