I am specifying a sample of weekly work records to be entered into a spreadsheet for an estimation of means on two variables. There are about 250 employees, I am only interested in weeks between a specific date and the present, the total universe of possible work weeks is 28,538. Because we wanted to assure that the sample was representative by employee and calendar quarter, the population was stratified by calendar quarter and employee, and random sampling with replacement was used within the strata to define a sample of 2190 employee weeks.
I recently learned that the data for the first year of the time period we're interested in is unavailable. The unavailable population data includes 50 weeks out of 341 weeks in the period of interest, and also includes 23 out of the 250 employees. Overall, of the 2190 lines specified in the sample as designed, about 175 lines are unavailable.
A biased sample representing one employee has already been drawn from the population, the obtained sample variance on the statistic of interest was 115.37, n=276.
I realize that the unavailability of data for a certain time period systematically biases the sample's representativeness across calendar quarters, and that bias is introduced by the fact that 23 employees are not represented at all. My question is, what other concerns are introduced by this limitation in the availability of data from which to sample?
My statistics experience comes from laboratory experimental design; I now find myself charged with questions regarding sampling and power in a naturalistic environment, any insight would be most helpful. Thanks.