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Weighting Results

One popular method for collecting data about daily activities is called experience sampling (Csikszentmihalyi and Larson 1987; Hektner et al. 2007). You give a sample of people a beeper or a cell phone. They carry it around and you beep or call them at random times during the day. They fill out a little form (either on paper or on a PDA) about what they’re doing at the time. (We’ll look more closely at this method in chapter 14.)

Suppose you want to contrast what people do on weekends with what they do during the week. If you beep people, say, eight times during each day, you’ll wind up with 40 reports for each person for the 5-day workweek but only 16 forms for each person for each 2-day weekend because you’ve sampled the two strata—weekdays and weekends— proportionately.

If you want more data points for the weekend, you might beep people 12 times on Saturday and 12 times on Sunday. That gives you 24 data points, but you’ve disproportionately sampled one stratum. The weekend represents 2/7, or 28.6% of the week, but you’ve got 64 data points and 24 of them, or 37.5%, are about the weekend. Before comparing any data across the strata, you need to make the weekend data and the weekday data statistically comparable.

This is where weighting comes in. Multiply each weekday data point by 1.50 so that the 40 data points become worth 60 and the 24 weekend data points are again worth exactly 2/7 of the total.

You should also weight your data when you have unequal response rates in a stratified sample. Suppose you sample 200 farmers and 200 townspeople in a rural African district where 60% of the families are farmers and 40% are residents of the local town. Of the 400 potential informants, 178 farmers and 163 townspeople respond to your questions. If you compare the answers of farmers and townspeople on a variable, you’ll need to weight each farmer’s data by 178/163 = 1.09 times each herder’s data on that variable. That takes care of the unequal response rates.

Then, you’ll need to weight each farmer’s data as counting 1.5 times each townsper- son’s data on the variable. That takes care of the fact that there are half again as many farmers as there are people living in town. Weighting is a simple procedure available in all major statistical analysis packages.

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