Q USE OF PROCESS DATA TO DETERMINE THE NUMBER OF CALL ATTEMPTS IN A TELEPHONE SURVEY Annica Isaksson Linköping University, Sweden Peter Lundquist Statistics Sweden Daniel Thorburn Stockholm University, Sweden

Q The Problem Consider a telephone survey of individuals, in which a maximum number A of call attempts is to be made to sampled individuals. Part of a larger problem of designing efficient call scheduling algorithms. HOW SHALL A BE CHOSEN?

Q Prerequisites (Single-occasion survey) Direct sampling from a frame with good population coverage Estimation of a population total by the direct weighting estimator Response set after A call attempts Inclusion probability for individual k Estimated response probability for individual k after A call attempts Observed value for individual k (proxy for the true value µ k )

Q The Survey as a Three-Stage Process Stage 1: Sample selection Stage 2: Contact and response Maximally A call attempts are made. Individuals respond in accordance with an unknown response distribution. Stage 3: Measurement Observed values are related to the true values according to a measurement error model.

Q Response Model all individuals within the same group have the same probability of responding individuals respond independently of each other individuals respond independently of each other after different numbers of call attempts The sample can be divided into H s response homogeneity groups (RHG) such that, for all A, given the sample,

Q Measurement Error Model For an individual k in RHG h, given the sample and that the individual responds at call attempt a, Indicates if individual k responds at attempt a=a k Random interviewer effect with expectation 0 and variance Random response error with expectation 0 and variance True value for individual k

Q Bias and Variance Bias if the RHG model does not hold: The variance of is derived in the paper Sample covariance between response probabilities and design weighted true values Average response probability within RHG

Q Cost Function

Q Optimum A for RHG h Assume: of the costs are allocated to RHG h

Q Optimum A for RHG h: Result The optimum number of call attempts for RHG h is the number A h that gives the lowest value on the function

Q Our Data Annual salary 2006 according to the Swedish Tax Register (our y) Process data from WinDati (WD). LFS data from March-Dec. 2007, supplemented with: Note: not all WD events are call attempts

Q Data Processing and Estimation. Each monthly sample viewed as a SRS Parameter: = total annual salary 2006 Bias within RHG h and month l estimated by

Q Relative Bias, Monthly Averages

Q =.002 = 55,267,619,616 = 110,979,155. Measurement Error Model Parameters Intraclass correlation, ICC (Biemer and Trewin, 1997):

Q No Bias, ICC =.002

Q Bias, ICC =.002

Q Tentative Results Efficient planning requires high-quality data on processes and costs Perhaps the choice of A should be based on variance rather than MSE

Q Discussion and Future Work Do the results hold for other study variables, other survey settings? Improved models for measurement errors, response and costs? Develop a planning tool?

Q Thank you for your attention! Annica Isaksson, Peter Lundquist,