SAMPLING INFORMATION FOR CONTINUOUS MONITORING The telephone survey design for continuous monitoring involved RDD sample design issues of some complexity. The sample objective was a uniform number of interviews in each "week" (a 17 day interviewing period) of a 46 week study period. We should be able to treat each of the weekly samples more or less independently. That is, the user should be able to take the weekly samples and aggregate them in various ways to represent time periods (months, quarters, pre-primary intervals) of interest to their research. The constraints on the sample design were also clear: time and money. Given the strong relationship between time and cost in telephone interviewing operations, the chosen sample design had to be one which minimized the amount of time that interviewers must spend in reaching respondent households. A proven method for reducing contact time is the two-stage RDD design originally suggested by Warren Mitofsky and Joe Waksberg. Very briefly, this design utilizes the A.T.& T. listing of telephone central office codes. Each record on the listing is an area code-central office code combination, e.g., 313-764; thus each record represents 10,000 distinct telephone numbers (e.g., 313-764-0000 through 313-764-9999). Another way to put it is that each record represents 100 clusters of 100 consecutive telephone numbers (0000-0099,0100-0199, etc.). Each primary selection is one such group of 100 consecutive telephone numbers, designated by randomly generating a single 4-digit number. For example if (313) 764-4424 is generated, the cluster containing numbers 4400-4499 is tentatively designated for selection. These primary numbers are called; if they are not working household numbers, the clusters in which they fall are not selected. If they are working household numbers, their clusters are selected into the sample and a specified number of additional four-digit numbers within the same cluster is generated. For example, if the desired sample size is nine, eight more 4-digit numbers within the hundred series would be selected. While the Waksberg-Mitofsky method is cost-effective, it sacrifices something in precision because of its clustered nature. The NES implementation of this design for Continuous Monitoring spreads the use of each primary stage sample one-hundred series over the 46 week course of the study -- maximizing the distribution of the sample and minimizing the clustering effects for short time interval analyses. At the end of the 46-week study period, the complete sample will contain roughly 700 primary stage numbers (clusters) of 5 interviews each. In the Waksberg-Mitofsky two-stage selection, the several numbers selected from each cluster at the second stage are used within the same sample period. In the NES variation, each cluster that is selected produces one telephone number per week. (This telephone number translates into a label of a sample coversheet). When there is an interview or some other kind of final disposition of the coversheet, the cluster is not used further in the sample week. Clusters of primary numbers are in the sample for two weeks, then rotate out for 8 weeks. The assignment of clusters produces a 50% overlap from week to week. The intent of this overlap is to introduce some correlation among observations for short, adjacent intervals of time. If successful, the time 1 to time 2 correlations will yield improved precision for estimates of change between the two periods. As the study design is implemented, it is important to note that certain coversheet dispositions mean that a cluster can be "re-dialed" within the sample week. For example, if the telephone number on the coversheet is of a business (non-household) then the next number in the primary number series can replace it. Other redialing situations are non-working numbers or non-sample residences (institutions). Some sample coversheets, even though they do not yield an interview, cannot be replaced. These include refusals, non-interviews of valid respondents, and households with no eligible respondents. Once a household is reached, selection of respondents within the household proceeds by listing all persons within that household (male, oldest to youngest; female, oldest to youngest); determining which of the residents are eligible (18 on election day, U. S. citizens) and using a Kish selection table to randomly determine the respondents. The method results in slightly unequal probabilities of selection. That is, respondents in households with TWO telephone numbers are twice as likely to be selected as those with only one telephone number. Also, respondents from households with TWO eligible residents are only half as likely to be selected as respondents who are the only eligible adult. The NES staff has compared weighted and unweighted frequency distributions for a number of variables. Results indicate that the data may be treated as an equal probability sample, i.e., that selection weights are not required. Those interested in a further discussion of the point should see working paper #5. (See Appendix C).