Support #886

Zero weights and statistical power

Added by Eric Emerson almost 5 years ago. Updated over 4 years ago.

Start date:
% Done:




I'm interested in data contained the harassment modules (in Waves 1, 3, 5 and 7), but am concerned about the significant reduction in statistical power arising from the increasing proportion of respondents who are assigned values of 0 in w_ind5mus_xw. I understand from a previous thread (#877) that ..... 'The provision of weights requires the ability to estimate probabilities of continuing to respond over multiple waves. This is true of cross-sectional weights as well as longitudinal ones, as they are derived from the longitudinal ones (how this was done is described in section of the User Guide). In consequence, a person in a household where there is no person who has been enumerated at every wave up to wave w will get a weight of zero. Such people should not be given a weight, as the weights for all other sample members are calculated in a way that compensates for these "missing" people.'

However, the 'compensation' appears to also result in a significant loss of statistical power. Taking as base the unweighted number of respondents who provide a valid answer to the 'attacked' items, the weighted population size has reduced from 92% of actual respondents in W1 (7418/8072) to just 27% in W7 (2711/9973). The resulting reduction in power is of concern and given the rationale outlined above, will continue to increase over time as the % of households in which someone has been enumerated at every wave will continue to diminish. It also seems rather wasteful of people's time that the responses of the majority of participants is, through the weighting process, assigned to a statistical waste bin!

Be very grateful if you could suggest any ways round this problem.

Many thanks


Also available in: Atom PDF