Showing papers by "Duncan Thomas published in 1999"

Early Test Scores, Socioeconomic Status and Future Outcomes

Abstract: This paper examines the long-term effects of early test scores using data from the British National Child Development Survey. We show that test scores measured as early as age 7 have significant effects on future educational and labor market outcomes. For example, men and women in the lowest quartile of the reading test score distribution have wages 20% lower at age 33 than those who scored in the highest quartile. We test several hypotheses about the interactions between socioeconomic status and high or low test scores at age 7. In terms of test scores, educational attainments, and employment at age 33, low-SES children reap both larger gains from having high age 7 test scores and smaller losses from having low age 7 test scores. The opposite is true among high-SES children who suffer larger losses from low scores and smaller gains from high scores. However we find little evidence of comparable interactive effects for wages.

The real costs of Indonesias economic crisis: preliminary findings from the Indonesia Family Life Surveys.

Abstract: Indonesia is at the center of dramatic political and economic upheaval. Projections put output in 1998 at 15% below its 1997 level and inflation at 75-80% for 1997. Riots and demonstrations flared in several Indonesian cities. After leading the country for more than a quarter of a century President Suharto resigned in May of 1998. Few Indonesians have remained untouched by these and other events of the last couple of years. The drought of 1997 the price shocks associated with the collapse of the rupiah and removal of subsidies and the income shocks arising from changes in demand combine to yield an extremely complex picture of substantial change throughout the society. The effects of the crisis on welfare of the population are nuanced and heterogeneous. They vary by region across socio-economic groups and across demographic groups. If policies are to succeed at mitigating the effects of the crisis the policies must be based on solid information about who has been affected how they have been affected and how they are changing their behaviors in response to the crisis. This study seeks to provide information on those topics. The results are based on data from the Indonesia family Life Survey (IFLS) an on-going longitudinal survey of individuals households and communities in Indonesia conducted by RAND in collaboration with UCLA and Lembaga Demografi. For the purpose of understanding how the economic crisis has affected welfare we compare the responses of individuals interviewed in the second half of 1997 to responses obtained through reinterviews with those same individuals in the second half of 1998. In the 1998 follow-up we succeeded at reinterviewing over 98% of the 1934 households from which data were collected in 1997. (excerpt)

Asymptotic Bias and Efficiency In Case-Control Studies of Candidate Genes and Gene-Environment Interactions: Basic Family Designs

Abstract: Case-control designs that use population controls are compared with those that use controls selected from their relatives (i.e., siblings, cousins, or "pseudosibs" based on parental alleles) for estimating the effect of candidate genes and gene-environment interactions. The authors first evaluate the asymptotic bias in relative risk estimates resulting from using population controls when there is confounding due to population stratification. Using siblings or pseudosibs as controls completely addresses this issue, whereas cousins provide only partial protection from population stratification. Next, they show that the conventional conditional likelihood for matched case-control studies can give asymptotically biased effect estimates when applied to the pseudosib approach; the asymptotic bias is toward the null and disappears with disease rarity. They show how to reparameterize the pseudosib likelihood so this approach gives consistent effect estimates. They then show that the designs using population or pseudosib controls are generally the most efficient for estimating the main effect of a candidate gene, followed in efficiency by the design using cousins. Finally, they show that the design using sibling controls can be quite efficient when studying gene-environment interactions. In addition to asymptotic bias and efficiency issues, family-based designs might benefit from a higher motivation to participate among cases' relatives, but these designs have the disadvantage that many potential cases will be excluded from study by having no available controls.

Early Test Scores, Socioeconomic Status and Future Outcomes

Abstract: This paper examines the long-term effects of early test scores using data from the British National Child Development Survey. We show that test scores measured as early as age 7 have significant effects on future educational and labor market outcomes. For example, men and women in the lowest quartile of the reading test score distribution have wages 20% lower at age 33 than those who scored in the highest quartile. We test several hypotheses about the interactions between socioeconomic status and high or low test scores at age 7. In terms of test scores, educational attainments, and employment at age 33, low-SES children reap both larger gains from having high age 7 test scores and smaller losses from having low age 7 test scores. The opposite is true among high-SES children who suffer larger losses from low scores and smaller gains from high scores. However we find little evidence of comparable interactive effects for wages.

Family-based association studies

Abstract: We review case-control designs for studying gene associations in which relatives of case patients are used as control subjects. These designs have the advantage that they avoid the problem of population stratification that can lead to spurious associations with noncausal genes. We focus on designs that use sibling, cousin, or pseudosibling controls, the latter formed as the set of genotypes not transmitted to the case from his or her parents. We describe a common conditional likelihood framework for use in analyzing data from any of these designs and review what is known about the validity of the various design and analysis combinations for estimating the genetic relative risk. We also present comparisons of efficiency for each of the family-based designs relative to the standard population-control design in which unrelated controls are selected from the source population of cases. Because of overmatching on genotype, the use of sibling controls leads to estimates of genetic relative risk that are approximately half as efficient as those obtained with the use of population controls, while relative efficiency for cousin controls is approximately 90%. However, we find that, for a rare gene, the sibling-control design can lead to improved efficiency for estimating a G x E interaction effect. We also review some restricted designs that can substantially improve efficiency, e.g., restriction of the sample to case-sibling pairs with an affected parent. We conclude that family-based case-control studies are an attractive alternative to population-based case-control designs using unrelated control subjects.

Correcting for exposure measurement error in a reanalysis of lung cancer mortality for the Colorado Plateau Uranium Miners cohort.

Abstract: The exposure estimates used to date for the analysis of lung cancer mortality in the Colorado Plateau Uranium Miners cohort were developed from radon progeny measurements taken in mines beginning in 1951. Since uranium miners were often exposed over long periods of time and since mines were not continuously monitored, much extrapolation and/or interpolation of measured dose-rates was needed in order to develop estimates of exposure for each of the miners in the cohort. We have recently re-examined the interpolation scheme used to create the histories in the light of the fit of a statistical model for the radon progeny measurements taken in mines within the Plateau, and we have computed revised exposure estimates for the large majority of miners in the cohort. This report describes the use of these new model-based revised exposure estimates in the analysis of lung cancer mortality, using follow-up data current through 1990. Specific issues addressed here are (1) the strength of the association between exposure and risk of lung cancer mortality; (2) effects of attained age and time since exposure upon risk of lung cancer mortality; and (3) exposure-rate effects upon risk. Results using the revised exposure estimates are compared to those obtained fitting the same models using the original Public Health Service (PHS) exposure estimates. We found evidence that the new exposure histories provide a better fit to the lung cancer mortality data than do the histories based upon the original PHS dose-rate estimates. In general, the new results show a stronger overall relationship (larger slope estimate) between lung cancer mortality and exposure per unit exposure compared to those obtained with the original estimates, while displaying similar age at exposure and time since exposure effects. In the reanalysis the impact of low dose-rate exposure is found to be relatively unchanged before and after exposure error correction, while the estimate of the effect of high dose-rate exposure is considerably increased. Even after applying our measurement error corrections, evidence of inverse dose-rate effects is found, since the estimate of the impact of high dose-rate exposure is still below that of the low dose-rates. The magnitude and statistical significance, however, of the dose-rate effect estimates are diminished when fit using the revised exposure estimates.

Cohort Studies for Characterizing Measured Genes

Abstract: We describe the advantages of using established cohort studies that have collected blood samples to investigate the role of genes in the etiology of cancer. These studies include the cost-efficiency and reliability of nested case‐control substudies from the cohort for exploration of gene‐disease associations and gene‐environment interactions as well as gene penetrance. Also, the cohort may serve as a well-defined “minipopulation” from which to study population stratification and molecular markers of ethnicity. We conclude that cohort studies can play a significant role in assessing the role of genetic markers for common tumors or multiple cancer sites. [Monogr Natl Cancer Inst 1999;26:39‐42] Many open questions exist about the importance of genetics in causing cancer and about the degree to which genetic variation can explain the variation in cancer risk across different populations. Estimates of familial risk and penetrance for putative major genes can be obtained from family studies via segregation analysis (1,2) or, once localized, via joint segregation and linkage analysis (3). Once the gene has been cloned, it is of interest to assess the role of the gene in cancer etiology in the general population. In some circumstances, family studies can be used to estimate penetrance (4). But, to assess relative and attributable risk in the general population, population case‐ control studies have been the main approach used over the past decade to evaluate the effects of common genetic polymorphisms on cancer risk (5). Case‐control studies are particularly appealing when large numbers of cases need to be rapidly accrued or when time-consuming and resource-intensive exposure assessment is required. In studies of genetic factors, these advantages of the case‐control design are not reduced by potential information biases, which may occur more commonly for certain exposures (i.e., dietary) assessed in case‐control studies than in prospective cohort studies. Cohort studies may also be used to evaluate genetic effects and may have some important advantages over case‐control studies. Even if a case‐control study might be more appropriate for answering a question about multiple exposures obtained

The Intergenerational Transmission of “Intelligence”: Down the Slippery Slopes of The Bell Curve

Abstract: Herrnstein and Murray report that conditional on maternal “intelligence” (AFQT scores), child test scores are little affected by variations in socioeconomic status. Using the same data, we demonstrate that their finding is very fragile. We explore the effect of adopting a more representative sample of children, including blacks and Latinos, allowing nonlinearities in the relationships, and incorporating richer measures of socioeconomic status. Making any one of these changes overturns their finding: Socioeconomic status and child test scores are positively ad significantly related. Evidence is presented suggesting AFQT scores are likely better markers for family background than “intelligence.”

Measuring Change in Indonesia

Abstract: After almost three decades of sustained economic growth, Indonesia is currently in the midst of a major economic and financial crisis. This paper seeks to contribute new evidence on three questions: who has been affected most by the crisis, how they have been affected and how they have responded to the crisis.

Study-design issues in the development of the University of Southern California Consortium's Colorectal Cancer Family Registry.

Abstract: The University of Southern California Consortium is a participating center in the National Cancer Institute's Collaborative Family Registry for Colorectal Cancer Studies (CFRCCS). Because data collection takes time, money, and effort, all of which are in short supply, we first defined our research objectives and then attempted to design our registry to enable us to address these objectives in an efficient manner. We decided on a family-based design, and our objectives are to characterize cloned genes that are generally accepted causes of colorectal cancer, to assess putative candidate genes, to map new genes, and to conduct prevention trials in high-risk subjects. For the gene characterization objectives, our primary aim is to estimate gene frequency and penetrance, with a secondary aim to investigate factors that may affect penetrance (allele-specific effects plus gene-gene and gene-environment interactions). We describe a multiple-stage design to select families into the registry. After a family is selected into the registry, we collect questionnaire data and blood samples on selected subjects only, and we tailor data collection decisions to each family (given who is affected and who is available) to optimize power per unit effort and cost. We also discuss practical decisions faced by our registry, including 1) defining a reference period for use in questionnaires; 2) deciding whether or not to establish cell lines and, if so, on whom; and 3) determining which cases should be tested for microsatellite instability. Finally, we address the appropriate use of data derived from high-risk clinics, within more broadly defined, population-based research.