The use of the logistic regression model to predict the probability of response and create non-response weights is classic. In most cases, the model is estimated using socio-demographic variables and all units in the selected sample. However, substantive analyses are often restricted to a sub-group of the sample. This paper investigates whether weights are more effective if they are designed using variables correlated with the response propensity in the sub-group in question and sample units in the selected sub-group using data from the British Household Panel Survey (BHPS). The findings demonstrate that, for some estimates, the tailored weights results in significantly different results than the usual weights.
Non-response bias Weighting variables Well-being Life satisfaction