Linking public issues with private troubles: panel studies in developing countries

Accompanying the call for increased evidence-based policy the developed world is implementing more longitudinal panel studies which periodically gather information about the same people over a number of years. Panel studies distinguish between transitory and persistent states (e.g. poverty, unemployment) and facilitate causal explanations of relationships between variables. However, they are complex and costly. A growing number of developing countries are now implementing or considering starting panel studies. The objectives of this paper are to identify challenges that arise in panel studies, and to give examples of how these have been addressed in resource-constrained environments. The main issues considered are: the development of a conceptual framework which links macro and micro contexts; sampling the cohort in a cost-effective way; tracking individuals; ethics and data management and analysis. Panel studies require long term funding, a stable institution and an acceptance that there will be limited value for money in terms of results from early stages, with greater benefits accumulating in the study's mature years. Copyright © 2003 John Wiley & Sons, Ltd.

Attrition in the Swiss Household Panel: Is change associated with later drop-out?

This study examines the importance of change in characteristics and circumstances of households and household members for contact and cooperation patterns. The literature suggests that there might be an underrepresentation of change in panel studies, because respondents facing more changes would be more likely to drop out. We approach this problem by analysing whether previous changes are predictive of later attrition or temporary drop-out, using eleven waves of the Swiss Household Panel (1999-2009). Our analyses support previous findings to some extent. Changes in household composition, employment status and social involvement as well as moving are associated mainly with attrition and less with temporary drop-out. These changes affect obtaining cooperation rather than obtaining contact, and tend to increase attrition.

Attrition in the Swiss Household Panel: Is change associated with drop-out?

This study examines the importance of change in characteristics and circumstances ofhouseholds and household members for contact and cooperation patterns. The literaturesuggests that there might be an underrepresentation of change in panel studies, becauserespondents facing more changes would be more likely to drop out. We approach this problemby analysing whether previous changes are predictive of later attrition or temporary drop-out,using eleven waves of the Swiss Household Panel (1999-2009). Our analyses supportprevious findings to some extent. Changes in household composition, employment status andsocial involvement as well as moving are associated mainly with attrition and less withtemporary drop-out. These changes affect obtaining cooperation rather than obtaining contact,and tend to increase attrition.

Gender differences at the transition to higher education between migrants and non-migrants: A comparison between Switzerland and France

Within Western societies women or girls meanwhile outperform men or boys with regard to attainments in primary and secondary education. For example concerning upper secondary degrees the share of females attaining the Matura approaches two thirds in Switzerland, while the share of females attaining the Baccalaureate exceeds fifty per cent in France. However, if transitions to higher education are regarded, the share of entitled females entering such institutions is significantly lower than among men in Switzerland. An opposite pattern is observed in France where females outperform men at this educational stage, too. With regard to migrant background, it has been shown by previous research focussing on secondary effects of ethnic origin that such youths enter the more demanding educational tracks (e.g. higher education) more often than their non-migrant peers if controlled for eligibility, their lower socioeconomic status and performances. However, so far only a few studies refer to the question of a possible gender gap regarding secondary effects of ethnic origin (e.g. Fleischmann et al., mimeo). Thus, with regard to a possible interaction of a migrant background and - for example - a female gender, it is important to note that in both countries many migrant groups have their origins in countries and regions where male advantage remains very strong. This is in particular the case for migrant groups from non-Western countries, e.g. Turkey, Algeria, Marocco or Tunisie, where gender gaps in the literacy rates of up to 18 per cent are still observed. In order to investigate the question of a possible disadvantages of women with a migrant background stemming from such countries when compared to non-migrant females two panel studies - the Tree data in Switzerland and the Panel d’élèves 1995 in France -, are analysed.

Combining Information from Multiple Sources in Bayesian Modeling

Surveys can collect important data that inform policy decisions and drive social science research. Large government surveys collect information from the U.S. population on a wide range of topics, including demographics, education, employment, and lifestyle. Analysis of survey data presents unique challenges. In particular, one needs to account for missing data, for complex sampling designs, and for measurement error. Conceptually, a survey organization could spend lots of resources getting high-quality responses from a simple random sample, resulting in survey data that are easy to analyze. However, this scenario often is not realistic. To address these practical issues, survey organizations can leverage the information available from other sources of data. For example, in longitudinal studies that suffer from attrition, they can use the information from refreshment samples to correct for potential attrition bias. They can use information from known marginal distributions or survey design to improve inferences. They can use information from gold standard sources to correct for measurement error.

This thesis presents novel approaches to combining information from multiple sources that address the three problems described above.

The first method addresses nonignorable unit nonresponse and attrition in a panel survey with a refreshment sample. Panel surveys typically suffer from attrition, which can lead to biased inference when basing analysis only on cases that complete all waves of the panel. Unfortunately, the panel data alone cannot inform the extent of the bias due to attrition, so analysts must make strong and untestable assumptions about the missing data mechanism. Many panel studies also include refreshment samples, which are data collected from a random sample of new

individuals during some later wave of the panel. Refreshment samples offer information that can be utilized to correct for biases induced by nonignorable attrition while reducing reliance on strong assumptions about the attrition process. To date, these bias correction methods have not dealt with two key practical issues in panel studies: unit nonresponse in the initial wave of the panel and in the

refreshment sample itself. As we illustrate, nonignorable unit nonresponse

can significantly compromise the analyst's ability to use the refreshment samples for attrition bias correction. Thus, it is crucial for analysts to assess how sensitive their inferences---corrected for panel attrition---are to different assumptions about the nature of the unit nonresponse. We present an approach that facilitates such sensitivity analyses, both for suspected nonignorable unit nonresponse

in the initial wave and in the refreshment sample. We illustrate the approach using simulation studies and an analysis of data from the 2007-2008 Associated Press/Yahoo News election panel study.

The second method incorporates informative prior beliefs about

marginal probabilities into Bayesian latent class models for categorical data.

The basic idea is to append synthetic observations to the original data such that

(i) the empirical distributions of the desired margins match those of the prior beliefs, and (ii) the values of the remaining variables are left missing. The degree of prior uncertainty is controlled by the number of augmented records. Posterior inferences can be obtained via typical MCMC algorithms for latent class models, tailored to deal efficiently with the missing values in the concatenated data.

We illustrate the approach using a variety of simulations based on data from the American Community Survey, including an example of how augmented records can be used to fit latent class models to data from stratified samples.

The third method leverages the information from a gold standard survey to model reporting error. Survey data are subject to reporting error when respondents misunderstand the question or accidentally select the wrong response. Sometimes survey respondents knowingly select the wrong response, for example, by reporting a higher level of education than they actually have attained. We present an approach that allows an analyst to model reporting error by incorporating information from a gold standard survey. The analyst can specify various reporting error models and assess how sensitive their conclusions are to different assumptions about the reporting error process. We illustrate the approach using simulations based on data from the 1993 National Survey of College Graduates. We use the method to impute error-corrected educational attainments in the 2010 American Community Survey using the 2010 National Survey of College Graduates as the gold standard survey.

Design and evaluation of a panel os single-nucleotide polymorphisms in microRNA genomic regions for association studies in human disease

MicroRNAs (miRNA) are recognized posttranscriptional gene repressors involved in the control of almost every biological process. Allelic variants in these regions may be an important source of phenotypic diversity and contribute to disease susceptibility. We analyzed the genomic organization of 325 human miRNAs (release 7.1, miRBase) to construct a panel of 768 single-nucleotide polymorphisms (SNPs) covering approximately 1 Mb of genomic DNA, including 131 isolated miRNAs (40%) and 194 miRNAs arranged in 48 miRNA clusters, as well as their 5-kb flanking regions. Of these miRNAs, 37% were inside known protein-coding genes, which were significantly associated with biological functions regarding neurological, psychological or nutritional disorders. SNP coverage analysis revealed a lower SNP density in miRNAs compared with the average of the genome, with only 24 SNPs located in the 325 miRNAs studied. Further genotyping of 340 unrelated Spanish individuals showed that more than half of the SNPs in miRNAs were either rare or monomorphic, in agreement with the reported selective constraint on human miRNAs. A comparison of the minor allele frequencies between Spanish and HapMap population samples confirmed the applicability of this SNP panel to the study of complex disorders among the Spanish population, and revealed two miRNA regions, hsa-mir-26a-2 in the CTDSP2 gene and hsa-mir-128-1 in the R3HDM1 gene, showing geographical allelic frequency variation among the four HapMap populations, probably because of differences in natural selection. The designed miRNA SNP panel could help to identify still hidden links between miRNAs and human disease.

Pilot Studies for Development of an HIV Subtype Panel for Surveillance of Global Diversity

The continued global spread and evolution of HIV diversity pose significant challenges to diagnostics and vaccine strategies. NIAID partnered with the FDA, WRAIR, academia, and industry to form a Viral Panel Working Group to design and prepare a panel of well-characterized current and diverse HIV isolates. Plasma samples that had screened positive for HIV infection and had evidence of recently acquired infection were donated by blood centers in North and South America, Europe, and Africa. A total of 80 plasma samples were tested by quantitative nucleic acid tests, p24 antigen, EIA, and Western blot to assign a Fiebig stage indicative of approximate time from initial infection. Evaluation of viral load using FDA-cleared assays showed excellent concordance when subtype B virus was tested, but lower correlations for subtype C. Plasma samples were cocultivated with phytohemagglutinin (PHA)-stimulated peripheral blood mononuclear cells (PBMCs) from normal donors to generate 30 viral isolates (50-80% success rate for samples with viral load >10,000 copies/ml), which were then expanded to 10(7)-10(9) virus copies per ml. Analysis of env sequences showed that sequences derived from cultured PBMCs were not distinguishable from those obtained from the original plasma. The pilot collection includes 30 isolates representing subtypes B, C, B/F, CRF04_cpx, and CRF02_AG. These studies will serve as a basis for the development of a comprehensive panel of highly characterized viral isolates that reflects the current dynamic and complex HIV epidemic, and will be made available through the External Quality Assurance Program Oversight Laboratory (EQAPOL).

Consideration of three proposals to conduct research on possible health effects of radiation from nuclear weapon testing in Arizona, Nevada, and Utah, and nuclear weapon testing and studies related to health effects : an historical summary : responding to recommendations by the panel of experts on the archive of PHS documents /

Mode of access: Internet.