Differences in Efficiencies Between ABS and RDD Samples by Mode of Data Collection

Research on mode of administration of surveys increasingly appears in the literature. Little research includes comparisons by sample frame as well as by mode. This research examines differences in efficiency using two types of sample frames (address-based samples [ABS] or random digit dialing [RDD] samples) and multiple modes (web-based surveys, mailed questionnaire, and telephone interview) among adult respondents. Matching telephone numbers to addresses was conducted on both samples. A test of the effectiveness of making modifications to drop point locations in the ABS was also undertaken. A higher proportion of addresses were matched to telephone numbers in an ABS but with less accuracy than matching telephone numbers to addresses in an RDD sample. Costs per competed interview were lower using the RDD than when using the ABS. Efforts to specify apartment numbers in drop point locations in the ABS were not found to be cost effective. Overall, for both demographic and substantive question outcomes, survey frame has less of an impact than survey mode on measures of response rate and cost.

Disentangling monitoring programs: design, analysis, and application considerations

Monitoring programs are an essential tool for assessing and informing conservation efforts but the methods used to gather monitoring data directly influence results. This presents a challenge to conservation professionals when deciding on existing data to inform a given question. We illustrate the challenges of using monitoring data by comparing population trends from two large-scale avian monitoring programs in the western United States: the Breeding Bird Survey and Integrated Monitoring in Bird Conservation Regions programs. We used publicly available data to compare trend trajectory between 2008 and 2015 for 148 species across Colorado, Montana, and Wyoming. Trends were inconsistent for 62% of the comparisons, with species having opposite trends in 21 cases. The inconsistencies found within our species comparisons reflect the inherent differences between program sampling design and analytical approach. Periodically revisiting how and why we monitor natural resources is necessary to advance conservation and management as the lessons learned from long-standing programs guide the development of more recent efforts. Our results emphasize that prior to management actions and policy decisions, managers must be aware of both the sampling design and appropriate ecological inference of any monitoring program.

An Update on Using the Range to Estimate σ When Determining Sample Sizes

In this research, we develop a strategy for using a range estimator of σ when determining a sample size for estimating a mean. Previous research by Rhiel is extended to provide d_n values for use in calculating a range estimate of σ when working with sampling frames up to size 1,000,000. This allows the use of the range estimator of σ with "big data." A strategy is presented for using the range estimator of σ for determining sample sizes based on the d_n values developed in this study.

How to test hypotheses if you must

Drug development is not the only industrial-scientific enterprise subject to government regulations. In some fields of ecology and environmental sciences, the application of statistical methods is also regulated by ordinance. Over the past 20years, ecologists and environmental scientists have argued against an unthinking application of null hypothesis significance tests. More recently, Canadian ecologists have suggested a new approach to significance testing, taking account of the costs of both type I and type II errors. In this paper, we investigate the implications of this for testing in drug development and demonstrate that its adoption leads directly to the likelihood principle and Bayesian approaches.

Inclusion of mobile phone numbers into an ongoing population health survey in New South Wales, Australia: design, methods, call outcomes, costs and sample representativeness

BACKGROUND

In Australia telephone surveys have been the method of choice for ongoing jurisdictional population health surveys. Although it was estimated in 2011 that nearly 20% of the Australian population were mobile-only phone users, the inclusion of mobile phone numbers into these existing landline population health surveys has not occurred. This paper describes the methods used for the inclusion of mobile phone numbers into an existing ongoing landline random digit dialling (RDD) health survey in an Australian state, the New South Wales Population Health Survey (NSWPHS). This paper also compares the call outcomes, costs and the representativeness of the resultant sample to that of the previous landline sample.

METHODS

After examining several mobile phone pilot studies conducted in Australia and possible sample designs (screening dual-frame and overlapping dual-frame), mobile phone numbers were included into the NSWPHS using an overlapping dual-frame design. Data collection was consistent, where possible, with the previous years' landline RDD phone surveys and between frames. Survey operational data for the frames were compared and combined. Demographic information from the interview data for mobile-only phone users, both, and total were compared to the landline frame using χ2 tests. Demographic information for each frame, landline and the mobile-only (equivalent to a screening dual frame design), and the frames combined (with appropriate overlap adjustment) were compared to the NSW demographic profile from the 2011 census using χ2 tests.

RESULTS

In the first quarter of 2012, 3395 interviews were completed with 2171 respondents (63.9%) from the landline frame (17.6% landline only) and 1224 (36.1%) from the mobile frame (25.8% mobile only). Overall combined response, contact and cooperation rates were 33.1%, 65.1% and 72.2% respectively. As expected from previous research, the demographic profile of the mobile-only phone respondents differed most (more that were young, males, Aboriginal and Torres Strait Islanders, overseas born and single) compared to the landline frame responders. The profile of respondents from the two frames combined, with overlap adjustment, was most similar to the latest New South Wales (NSW) population profile.

CONCLUSIONS

The inclusion of the mobile phone numbers, through an overlapping dual-frame design, did not impact negatively on response rates or data collection, and although costing more the design was still cost-effective because of the additional interviews that were conducted with young people, Aboriginal and Torres Strait Islanders and people who were born overseas resulting in a more representative overall sample.

Multiple indicator cluster survey 2003 in Afghanistan: outdated sampling frame and the effect of sampling weights on estimates of maternal and child health coverage

Due to an urgent need for information on the coverage of health service for women and children after the fall of Taliban regime in Afghanistan, a multiple indicator cluster survey (MICS) was conducted in 2003 using the outdated 1979 census as the sampling frame. When 2004 pre-census data became available, population-sampling weights were generated based on the survey-sampling scheme. Using these weights, the population estimates for seven maternal and child healthcare-coverage indicators were generated and compared with the unweighted MICS 2003 estimates. The use of sample weights provided unbiased estimates of population parameters. Results of the comparison of weighted and unweighted estimates showed some wide differences for individual provincial estimates and confidence intervals. However, the mean, median and absolute mean of the differences between weighted and unweighted estimates and their confidence intervals were close to zero for all indicators at the national level. Ranking of the five highest and the five lowest provinces on weighted and unweighted estimates also yielded similar results. The general consistency of results suggests that outdated sampling frames can be appropriate for use in similar situations to obtain initial estimates from household surveys to guide policy and programming directions. However, the power to detect change from these estimates is lower than originally planned, requiring a greater tolerance for error when the data are used as a baseline for evaluation. The generalizability of using outdated sampling frames in similar settings is qualified by the specific characteristics of the MICS 2003-low replacement rate of clusters and zero probability of inclusion of clusters created after the 1979 census.