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Abstract
With the rapid advancement of IT and the changing times, Taiwan has been facing increasing coverage error in single-frame telephone surveys (whether by landline or cell phone) in recent years. Dual-frame telephone surveys can effectively reduce this deficiency. However, there is still no consensus on how to weight dualframe telephone samples in Taiwan.
This study uses data from a 2020 dual-frame telephone survey to compare several popular weighting approaches. The impact of these approaches on the variance and bias in both single-frame and dual-frame samples, as well as in overlap and screener designs, is discussed. Additionally, this study examines the differences between the estimates of the non-proportion dual-frame sample allocation to provide practical recommendations.
The results indicate the following: (1) if the sample allocation of the dualframe samples is in nearly equal proportions, minor differences occur in the weighting loss between the overlap and screener designs. Only the post-stratified estimating procedure reveals some differences in the estimates with other designs. (2) If the sample allocation of the dual-frame samples is in unequal proportions, such as one single-frame national sample and the others are only 1/3 or 1/2 of the former, then after calibration, the weighting loss is only slightly increased, and these approaches produce only tiny differences in the calibrated estimates between the combinations.
Abstract
Goodness-of-fit tests allow us to examine if the sample at hand is representative enough of the population to ensure accurate statistical inferences of parameters. When the sample fails the tests, survey researchers often appeal to reweighting as a remedy. Post-stratification and raking are perhaps the two most popular weighting methods. However, post-stratification requires the knowledge of multivariate joint distribution of the population when more than one post-stratifying variable is considered. Without such detailed information, raking comes as a rescue since it requires only the knowledge of marginal distributions of selected variables. Popular as it may be, raking takes no account of associations among post-stratifying variables. Furthermore, it relies heavily on Chi-squared tests and a pre-selected p-value (usually 0.5) as the stopping rule of iteration, an ad hoc rule justified only by convenience. This article proposes a third way of Weighting, which we call it the minimum-discrimination-information (MDI) method. MDI approach finds optimal (in terms of minimum cross-entropy) relative weights by treating sample joint distribution as prior and known population marginal distributions as constraints. We first explain the rationale behind this proposed MDI method and then use TEDS 2001 survey data to compare the estimates of raking and MDI weights. We find that nearly 70 percent of the latter indeed replicate the Census 2000 population joint distribution better than the former. We thus conclude that MDI method is an approach worth further theoretical
Abstract
With the increase of cell phone usage in recent years, traditional landline surveys face a problem of incomplete coverage. It is now necessary to conduct dual-frame telephone surveys that includes cell phone samples and landline samples. Designing a dual-frame telephone survey requires a decision on the sample allocation. The allocation of the sample to the dual-frame associates with the unequal weighting effect and the survey cost. Therefore, this study aimed to illustrate an optimal allocation of respondents from landline and cellphone frames that result in the lowest unequal weight effect (i.e., the highest effective sample size) for a given cost by using the relative unit cost of obtaining a cell respondent compared to a landline respondent from a comparison study of survey cost, and an unequal weighting effect from “Public Value and Electronic Governance.” The results suggested that the optimal design will have 64.18% of the sample completes from the landline frame, and 35.82% of the sample completes from the cellphone frame in a cell-phone-only screened design. Additionally, this paper shows that the sample sizes of cell phone only could be a function of unequal weight effect and survey cost. Thus, the organizer of the cell-phoneonly screened design could substitute parameters into the function depending on different situations.
