Estimating nonresponse bias and mode effects in a mixed mode survey

In mixed-mode surveys, it is difficult to separate sample selection differences from mode-effects that can occur when respondents respond in different interview settings. This paper provides a framework for separating mode-effects from selection effects by matching very similar respondents from different survey modes using propensity score matching. The answer patterns of the matched respondents are subsequently compared. We show that matching can explain differences in nonresponse and coverage in two Internet-samples. When we repeat this procedure for a telephone and Internet-sample however, differences persist between the samples after matching. This indicates the occurrence of mode-effects in telephone and Internet surveys. Mode-effects can be problematic; hence we conclude with a discussion of designs that can be used to explicitly study mode-effects

Standard survey methods for estimating colony losses and explanatory risk factors in Apis mellifera

This chapter addresses survey methodology and questionnaire design for the collection of data pertaining to estimation of honey bee colony loss rates and identification of risk factors for colony loss. Sources of error in surveys are described. Advantages and disadvantages of different random and non-random sampling strategies and different modes of data collection are presented to enable the researcher to make an informed choice. We discuss survey and questionnaire methodology in some detail, for the purpose of raising awareness of issues to be considered during the survey design stage in order to minimise error and bias in the results. Aspects of survey design are illustrated using surveys in Scotland. Part of a standardized questionnaire is given as a further example, developed by the COLOSS working group for Monitoring and Diagnosis. Approaches to data analysis are described, focussing on estimation of loss rates. Dutch monitoring data from 2012 were used for an example of a statistical analysis with the public domain R software. We demonstrate the estimation of the overall proportion of losses and corresponding confidence interval using a quasi-binomial model to account for extra-binomial variation. We also illustrate generalized linear model fitting when incorporating a single risk factor, and derivation of relevant confidence intervals

The prevalence of genital warts in the Baltic countries : Findings from national cross-sectional surveys in Estonia, Latvia and Lithuania

Objectives: To assess the prevalence and correlates of self-reported genital warts (GWs) among women and men aged 18-45 years in the Baltic countries. Methods: In 2011-2013 we performed a cross-sectional survey using a self-administered questionnaire to collect information on the history of clinically diagnosed GWs, sociodemographic characteristics and sexual behaviour. Probability sampling methods were used to invite 16 959 individuals representing the general population, of whom 7760 (45.8%) participated (Estonia: 1967 women, 1221 men; Latvia: 1525 women, 1525 men; Lithuania: 1522 women). Results: The estimated lifetime prevalence of clinically diagnosed GWs in women was 4.6% (95% CI 3.8 to 5.5) in Estonia, 2.9% (95% CI 2.0 to 3.6) in Latvia and 1.5% (95% CI 1.2 to 2.0) in Lithuania. Among men, the corresponding values were 2.8% (95% CI 1.9 to 4.0) in Estonia and 1.9% (95% CI 1.3 to 2.6) in Latvia. The mean age at first episode of clinically diagnosed GW was 24.6 years (95% CI 23.6 to 25.5) for women and 24.5 years (95% CI 22.9 to 26.0) for men. A lifetime history of clinically diagnosed GW was associated with a history of sexually transmitted infections other than GW (adjusted OR (AOR) 3.0, 95% CI 2.1 to 4.3 for women; AOR 5.3, 95% CI 3.0 to 9.2 for men), and a higher number (5+) of lifetime sexual partners (AOR 2.9, 95% CI 1.9 to 4.2 for women; AOR 2.1, 95% CI 1.2 to 3.9 for men). Men living comfortably within their household income had higher odds for GW (AOR 1.9, 95% CI 1.1 to 3.2). Conclusions: Our estimated prevalence of clinically diagnosed GWs was lower than estimates from the general population of other European countries.publishersversionPeer reviewe

Treatment decision-making and the form of risk communication: results of a factorial survey

BACKGROUND: Prospective users of preventive therapies often must evaluate complex information about therapeutic risks and benefits. The purpose of this study was to evaluate the effect of relative and absolute risk information on patient decision-making in scenarios typical of health information for patients. METHODS: Factorial experiments within a telephone survey of the Michigan adult, non-institutionalized, English-speaking population. Average interview lasted 23 minutes. Subjects and sample design: 952 randomly selected adults within a random-digit dial sample of Michigan households. Completion rate was 54.3%. RESULTS: When presented hypothetical information regarding additional risks of breast cancer from a medication to prevent a bone disease, respondents reduced their willingness to recommend a female friend take the medication compared to the baseline rate (66.8% = yes). The decrease was significantly greater with relative risk information. Additional benefit information regarding preventing heart disease from the medication increased willingness to recommend the medication to a female friend relative to the baseline scenario, but did not differ between absolute and relative risk formats. When information about both increased risk of breast cancer and reduced risk of heart disease were provided, typical respondents appeared to make rational decisions consistent with Expected Utility Theory, but the information presentation format affected choices. Those 11% – 33% making decisions contrary to the medical indications were more likely to be Hispanic, older, more educated, smokers, and to have children in the home. CONCLUSIONS: In scenarios typical of health risk information, relative risk information led respondents to make non-normative decisions that were "corrected" when the frame used absolute risk information. This population sample made generally rational decisions when presented with absolute risk information, even in the context of a telephone interview requiring remembering rates given. The lack of effect of gender and race suggests that a standard strategy of presenting absolute risk information may improve patient decision-making

Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136730/1/soin12168_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136730/2/soin12168.pd