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Table 2 Specifications of the parameters in the logistic regression models used to impose missing data under the missing at random scenarios

From: Multiple imputation methods for handling missing values in a longitudinal categorical variable with restrictions on transitions over time: a simulation study

Variable Odds Ratio
MAR (weak) MAR (strong)a
  Model A Equation 5b Model B Equation 6b Model A Equation 5b Model B Equation 6b
Maternal depression at wave j exp(ν1) = 1.67 exp(ω1) = 1.61 exp(ν1) = 2.80 exp(ω1) = 2.70
BMI for age z-scores at wave j + 1 exp(ν2) = 1.64 exp(ω2) = 1.58 exp(ν2) = 2.60 exp(ω2) = 2.50
  1. Abbreviations: BMI, body mass index; exp., exponential; MAR, missing at random
  2. aOdds ratio for MAR (Strong) = square of the Odds ratio for MAR (Weak)
  3. bModels A and B represent the logistic regression models used to generate missingness in maternal smoking from waves 1–5 under MAR, in all subsequent waves and intermittently respectively