Concurrently Assessing Survey Mode and Sample Size in Off‐Site Angler Surveys

Abstract

AbstractOff‐site angler surveys are commonly administered via two or more survey modes in the form of a mixed‐mode survey. Mixed‐mode surveys allow survey administrators to attain the benefits inherent to different survey modes, reduce total survey error, and control survey cost. However, these benefits can only be simultaneously attained after undertaking sample size planning. Sample size planning is a trade‐off analysis wherein a researcher concurrently assesses survey administration cost, the accuracy and precision of estimates, the magnitude and direction of biases, and variance of the test statistic to determine an optimal sample size. We used data from an off‐site angler survey administered to anglers targeting White Sturgeon Acipenser transmontanus to illustrate a systematic approach to sample size planning. Our survey design included a mixed‐mode design with three survey modes (e‐mail, mail, and telephone) and a two‐phase sampling design that had a first contact and a follow‐up contact with a subsample of nonrespondents. Sample size planning was undertaken in the form of a sensitivity analysis wherein four survey design alternatives were simulated and assessed based on four criteria (i.e., bias, precision, accuracy, and cost). We also incorporated tests for nonresponse bias and survey mode effect. We found that (1) response rates were lower for e‐mail surveys (22%) than for mail surveys and telephone surveys (39–44%); (2) nonresponse bias did not have a substantial effect on survey estimates from the mixed‐mode design; and (3) estimates (total effort and total catch) from the mail and e‐mail survey modes were significantly different, indicating a survey mode effect. The high variability of anglers’ annual catch made survey estimates highly imprecise at lower sample sizes. The level of acceptable error varies for each study. Therefore, a systematic approach to sample size planning is necessary to determine the point where acceptable error is reached while considering multiple survey design alternatives.Received September 25, 2016; accepted April 24, 2017 Published online June 19, 2017