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PubMed1996

Decomposing Water-Level Responses: Field Effects as Separate Influences

A previous study on water-level task performance using binomial mixture analyses showed that subgroups of subjects could be identified which used different response rules. Some subjects used a bottom parallel rule, others used a random-like rule, and still others used the correct response rule. The present study relates the water-level task performance of these subgroups to field effect influences. Subjects were 604 children and adolescents aged 7 to 15 years who responded to eight water-level and eight rod-and-frame task items. The results show that the water-level response distribution is influenced by the frame of the vessel. These field effects are relatively small if subjects maintain a fixed response rule, and they are large if subjects use a nonfixed random rule. Both field effects and response rules contribute to the behavior of subjects responding to water-level task items.

Journal Article↗
PubMed2003

Application of negative binomial modeling for discrete outcomes: a case study in aging research.

We present a case study using the negative binomial regression model for discrete outcome data arising from a clinical trial designed to evaluate the effectiveness of a prehabilitation program in preventing functional decline among physically frail, community-living older persons. The primary outcome was a measure of disability at 7 months that had a range from 0 to 16 with a mean of 2.8 (variance of 16.4) and a median of 1. The data were right skewed with clumping at zero (i.e., 40% of subjects had no disability at 7 months). Because the variance was nearly 6 times greater than the mean, the negative binomial model provided an improved fit to the data and accounted better for overdispersion than the Poisson regression model, which assumes that the mean and variance are the same. Although correcting the variance and corresponding test statistics for overdispersion is a standard procedure in the Poisson model, the estimates of the regression parameters are inefficient because they have more sampling variability than is necessary. The negative binomial model provides an alternative approach for the analysis of discrete data where overdispersion is a problem, provided that the model is correctly specified and adequately fits the data.

Activities of Daily Living↗
PubMed2005

A hierarchical Binomial-Poisson model for the analysis of a crossover design for correlated binary data when the number of trials is dose-dependent.

The differential reinforcement of a low-rate 72-seconds schedule (DRL-72) is a standard behavioral test procedure for screening a potential antidepressant compound. The data analyzed in the article are binary outcomes from a crossover design for such an experiment. Recently, Shkedy et al. (2004) proposed to estimate the treatments effect using either generalized linear mixed models (GLMM) or generalized estimating equations (GEE) for clustered binary data. The models proposed by Shkedy et al. (2004) assumed the number of responses at each binomial observation is fixed. This might be an unrealistic assumption for a behavioral experiment such as the DRL-72 because the number of responses (the number of trials in each binomial observation) is expected to be influenced by the administered dose level. In this article, we extend the model proposed by Shkedy et al. (2004) and propose a hierarchical Bayesian binomial-Poisson model, which assumes the number of responses to be a Poisson random variable. The results obtained from the GLMM and the binomial-Poisson models are comparable. However, the latter model allows estimating the correlation between the number of successes and number of trials.

Algorithms↗
PubMedDate not supplied

Upper and lower bounds for a serial dilution test.

A Poisson-binomial model estimates the concentration of a target microbe from a serial dilution test. The maximum likelihood procedure gives an equation whose solution equals the estimate of the concentration. This paper gives bounds for the solution to this equation that require only minimal calculations.

Chemistry Techniques, Analytical↗
PubMed2002

Measuring total health inequality: adding individual variation to group-level differences.

BACKGROUND: Studies have revealed large variations in average health status across social, economic, and other groups. No study exists on the distribution of the risk of ill-health across individuals, either within groups or across all people in a society, and as such a crucial piece of total health inequality has been overlooked. Some of the reason for this neglect has been that the risk of death, which forms the basis for most measures, is impossible to observe directly and difficult to estimate. METHODS: We develop a measure of total health inequality - encompassing all inequalities among people in a society, including variation between and within groups - by adapting a beta-binomial regression model. We apply it to children under age two in 50 low- and middle-income countries. Our method has been adopted by the World Health Organization and is being implemented in surveys around the world; preliminary estimates have appeared in the World Health Report (2000). RESULTS: Countries with similar average child mortality differ considerably in total health inequality. Liberia and Mozambique have the largest inequalities in child survival, while Colombia, the Philippines and Kazakhstan have the lowest levels among the countries measured. CONCLUSIONS: Total health inequality estimates should be routinely reported alongside average levels of health in populations and groups, as they reveal important policy-related information not otherwise knowable. This approach enables meaningful comparisons of inequality across countries and future analyses of the determinants of inequality.

Journal Article↗
PubMed2005

Sample size and power analysis for endometrial safety studies.

Endometrial safety studies are required for the approval of progestin components. The Committee for Proprietary Medicinal Products requirement is the actual percentage below 2% and the upper limit of the one-sided exact 95% confidence interval not more than 2% above the point estimate. The more recent U.S. Food and Drug Administration requirement is the actual percentage < or = 1% and the upper limit of the one-sided exact 95% confidence interval < or =4%. I studied the sample size and power needed to satisfy both requirements based on the exact confidence intervals for the binomial parameter and the Poisson parameter. I discovered that a larger sample size does not always lead to a higher power. I presented a best sample size that satisfies both requirements and recommended that the patient enrollment should be closely monitored during the study.

Aged↗
PubMed1997

A computer program for the analysis of over-dispersed counts and proportions.

Over-dispersed binary and count data occur frequently in many fields of application. Examples include occurrence of cavities in one or more teeth, and development of tumors in one or more animals of a litter. Methods of statistical analyses that ignore correlation between observations underestimate the standard errors. Consequently, coverage proportions of confidence intervals and significance levels of tests are distorted. To implement methods for the analysis of correlated binary or count data requires a level of sophistication for data analysis such that one can specify a model for over-dispersion and the correlation between observations. To analyze the over-dispersed binary or count data, one could postulate a specific statistical model and use maximum likelihood methods for the estimation of parameters. However, it may be preferable to employ an approach that does not rely on modeling because the true model is hard to know with confidence. Rao and Scott (J.N.K. Rao and A.J. Scott, Biometrics 48 (1992) 577-585)y and Scott and Rao (A.J. Scott and J.N.K. Rao, submitted for publication, 1995) proposed simple methods for analyzing correlated binary and count data exhibiting over-dispersion relative to a binomial and homogeneous Poisson model. This paper presents the SAS program to implement their methods to analyze over-dispersed binary and count data. To demonstrate the implementation and the usefulness of their methods, we present an application involving sensitivity of a monoclonal antibody and the number of mammary tumors developing in rats.

Animals↗
PubMedDate not supplied

[The brachial and cephalic perimeters as indicators of poverty and acute diarrhea in children under five years in Bogotá].

OBJECTIVE: To assess the relationship between nutritional status and some factors related with poverty (acute diarrhea and overcrowding) in children less than 6 years of age in Bogotá. METHODS: A community-based, cross-sectional study, was conducted during 2000 in the urban area of Bogotá, using a household interview survey. 3081 adults having in their homes children under five years were interviewed. This number of participants was calculated to obtain a representative sample of the city for estimating a binomial population parameter. A multistage sampling was carried out. The sample size was reduced to 2833 with the elimination of cases missing scores on dependent variables (DVs). Cephalic and brachial perimeters (continuous variables), used as a proxy of nutritional status (DVs), were selected as the main outcome measures. A 2 x 2 x 2 multivariate analysis of variance was performed on two DVs. Independent variables were overcrowding (as a measure of marginalization) and recent acute diarrhea. The analyses included sequential adjustment for nonorthogonality. RESULTS: DVs showed a low correlation (r=0.3) and a symmetric distribution. Evaluation of assumptions of linearity and multicollinearity were satisfactory. The omnibus test, using Wilk's criterion, showed that combined DVs were significantly affected by recent acute diarrhea (F=9.65 p=0.000), age less than 1 year (F=350.81 p=0.000) and the interaction acute diarrhea x overcrowding (F=6.25 p=0.000). In order to evaluate the impact of each main effect on the individual DVs, a Roy-Bargmann stepdown analysis was carried out. Homogeneity of regression was achieved for all components of the stepdown analysis. The brachial perimeter has a unique contribution to predict recent acute diarrhea (Roy-Bargmann F(1,1)=13.1 p=0.000). The cephalic perimeter has a unique contribution to predict acute diarrhea and overcrowding (Roy-Bargmann F(1,1)=10.22 p=0.001). CONCLUSIONS: Recent acute diarrhea and overcrowding are related with poor nutritional status. Brachial and cephalic perimeters could be attractive indicators of different varieties of nutritional deficiency.

Anthropometry↗
PubMed1992

Expression and distribution of cytosolic 6-phosphogluconate dehydrogenase isozymes in maize.

Maize (Zea mays L.) cytosolic 6-phosphogluconate dehydrogenase isozymes (EC 1.1.1.44; 6-PGD) are encoded by unlinked loci Pgd1 and Pgd2. Two families from a Robertson's Mutator line were isolated which have no detectable expression of Pgd2. These Pgd2-null mutants and a Pgd1-null line were used to generate plants homozygous for null alleles at both cytosolic 6-PGD loci. The specific activity of 6-PGD in the double-null mutant was between 20 and 30% of wild-type levels in root extracts. The double-null mutant was reproductively viable in a moderate environment, suggesting that wild-type levels of cytosolic 6-PGD activity are not essential for growth. Isozyme dimer ratios in roots, leaves, and scutellum were binomial and reflected the wild-type gene copy number. 6-PGD isozymes showed tissue- and cell type-specific expression.

Cytosol↗
PubMed1998

Analysis of the human sex ratio by using overdispersion models.

Data from nineteenth-century Germany are reanalyzed to determine how the probability for having a child of each sex changes with family size. The data, collected by A. Geissler, concern some 1 million birth registrations and 3.7 million births occurring in Saxony between 1876 and 1885. Three models are fitted to the data. "The multiplicative and beta-binomial models provide similar fits, substantially better than that of the double-binomial model. All models show that both the probability that the child is a boy and the dispersion are greater in larger families. There is also some indication that a point probability mass is needed for families containing children uniquely of one sex."

Demography↗
PubMed2005

Lipid content in the musculature of the lower leg: evaluation with high-resolution spectroscopic imaging.

A novel spectroscopic imaging method with high spectral and spatial resolution was developed for the specific goal of assessing muscle fat. Sensitivity to the methylene and methyl protons of fatty acids was improved by the use of a binomial 1 1 excitation pulse instead of the standard radiofrequency (RF) pulse. Acceptable measurement time is achieved by using a narrow spectral bandwidth (6 ppm). The spectral resolution is sufficient to resolve extramyocellular (EMCL) and intramyocellular (IMCL) lipids. A post-detection data processing scheme that permits correction of spectral artifacts caused by chemical shifts, spectral line aliasing, and magnetic field inhomogeneities is suggested. The lipid content in different lower leg muscles was evaluated. Muscle fiber orientation was taken into account in assessing quantities of EMCL and IMCL. The proposed technique allows small amounts of inhomogeneously distributed muscle lipids to be quantified.

Adult↗
PubMed2003

A district-based analysis of stillbirth and infant mortality rates in Italy: 1989-93.

Despite a substantial decline in stillbirth and infant mortality rates in Italy during the last century, there are still large differences between the north and south of the country. This paper analyses the geographical distribution of these rates in the period 1989-93 in terms of biological and social indicators with the aim of identifying possible sources for these differentials. Numbers of stillbirths, infant deaths and deliveries were available in an aggregate form by categories of biological and social factors for each of the 95 Italian administrative districts ('province') operative at the time. Substantial differences in stillbirth (SB) and infant mortality (IM) rates were found across geographical areas, with the lower rates found in the richer and more industrialised north and the higher ones in the more deprived south. Negative binomial regression models were used to study the geographical variations in these rates in terms of biological and social factors. The latter showed strong and significant effects on both SB and IM rates, even after controlling for biological factors. The effects of the biological factors, birthweight and maternal parity in particular, however, were found to differ across geographical areas. Further studies to investigate whether these results may be explained by differentials in health care should be considered.

Adult↗
PubMed1992

Assessing overdispersion and dose-response in the male dominant lethal assay.

In dominant lethal studies the primary variables of interest are typically expressed as discrete counts or proportions (e.g., live implants, resorptions, percent pregnant). Simple statistical sampling models for discrete data such as binomial or Poisson generally do not fit this type of data because of extra-binomial or extra-Poisson departures from variability predicted under these simple models. Extra-variability in the fetal response may originate from parental contributions. These can lead to over- or under-dispersion seen as, e.g., extra-binomial variability in the proportion response. Utilizing a large control database, we investigated the relative impact of extra-variability from male or female contributions on the endpoints of interest. Male-related effects did not seem to contribute to overdispersion in our database; female-related effects were, however, evidenced. Various statistical methods were considered to test for significant treatment differences under these forms of sampling variability. Computer simulations were used to evaluate these methods and to determine which are most appropriate for practical use in the evaluation of dominant lethal data. Our results suggest that distribution-free statistical methods such as a nonparametric permutation test or rank-based tests for trend can be recommended for use.

Analysis of Variance↗
PubMed2003

Conditional analysis of mixed Poisson processes with baseline counts: implications for trial design and analysis.

The design of clinical trials is typically based on marginal comparisons of a primary response under two or more treatments. The considerable gains in efficiency afforded by models conditional on one or more baseline responses has been extensively studied for Gaussian models. The purpose of this article is to present methods for the design and analysis of clinical trials in which the response is a count or a point process, and a corresponding baseline count is available prior to randomization. The methods are based on a conditional negative binomial model for the response given the baseline count and can be used to examine the effect of introducing selection criteria on power and sample size requirements. We show that designs based on this approach are more efficient than those proposed by McMahon et al. (1994).

Algorithms↗
PubMed2006

Effect of trauma systems on motor vehicle occupant mortality: A comparison between states with and without a formal system.

BACKGROUND: Population-based studies using a "before-and-after" methodology report a reduction in motor vehicle collision mortality with implementation of statewide trauma systems (TS). However, concurrent improvements in roads, cars, restraint systems, and changes in rates of drunk driving, socioeconomics, speed limits, urban or rural mix, and traffic density may also be responsible for the progressive reduction in mortality rates. We hypothesized that a statewide TS independently reduces injury mortality, irrespective of other factors. METHODS: Data were acquired from several federal agencies including the Centers for Disease Control (CDC), The National Highway Traffic Safety Administration (NHTSA), the United States Department of Transportation (DOT), and the United States Census Bureau. Age-adjusted motor vehicle occupant (MVO) death rates per 100,000 population were compared in states with and without a TS. Negative binomial regression was used to calculate risk ratios (RR) comparing mortality in TS and non-TS states after adjusting for effects of gender, race, primary seat belt laws, seat belt use, alcohol use, miles traveled, population density, per capita income, types of registered vehicles, and rural or urban mix. RESULTS: : The number of states with a TS increased from 7 in 1981 to 36 in 2002. Concurrently, nationwide MVO death rates decreased by 2.6 per 100,000 (95% confidence interval 1.2-3.9; p < 0.001). Income, primary seat belt laws, restraint use, speed limits, and rural or urban population distribution (p < 0.05 for all), were independent predictors of MVO mortality, but not presence of a TS (RR 0.95, 95% confidence interval 0.73-1.23; p = 0.68). CONCLUSIONS: MVO death rates have declined over time, and are lower in TS states. However, the cause is multi-factorial, and cannot be attributed solely to presence of TS. Further studies are needed to identify beneficial components of a statewide trauma system.

Accidents, Traffic↗
PubMed2003

Hierarchical Bayesian spatial modelling of small-area rates of non-rare disease.

We present Bayesian hierarchical spatial models for the analysis of the geographical distribution of a non-rare disease or event. The work is motivated by the need for ascertaining regional variations in health services outcomes and resource use and for assessing the potential sources of these variations. The models discussed herein readily accommodate random spatial effects and covariate effects. We discuss Bayesian inferential framework and implementation of a hybrid Markov chain Monte Carlo method for full Bayesian model inference. The methods are illustrated through an analysis of regional variation in chronic lung disease (CLD) rates among neonatal intensive care unit (NICU) patients across Canada. Specifically, we first present a random effects binomial model for spatially correlated CLD rates, with random spatial effects accounting for latent or covariate effects. These random spatial effects depict regional or spatial variation in chronic lung disease occurrence. We then extend this model to include covariates. With this extension, we assess residual spatial effects and the extent to which risk factors such as illness severity at NICU admission, low birth weight, and very low birth weight influence the CLD rate variation.

Bayes Theorem↗
PubMed1991

Analysis of trinomial responses from reproductive and developmental toxicity experiments.

This paper presents a Dirichlet-trinomial distribution for modelling data obtained from reproductive and developmental studies. The common endpoints for the evaluation of reproductive and developmental toxic effects are the number of dead fetuses, the number of malformed fetuses, and the number of normal fetuses for each litter. With current statistical methods for the evaluation of reproductive and developmental effects, the effect on the number of deaths and the effect on the number of malformations are analyzed separately. The Dirichlet-trinomial model provides a procedure for the analysis of multiple endpoints simultaneously. This proposed Dirichlet-trinomial model is a generalization of the beta-binomial model that has been used for handling the litter effect in reproductive and developmental experiments. Likelihood ratio tests for differences in the number of deaths, the number of malformations, and the number of normals among dosed and control groups are derived. The proposed test procedure based on the Dirichlet-trinomial model is compared with that based on the beta-binomial model with an application to a real data set.

Abnormalities, Drug-Induced↗
PubMed2007

Methods for improving regression analysis for skewed continuous or counted responses.

Standard inference procedures for regression analysis make assumptions that are rarely satisfied in practice. Adjustments must be made to insure the validity of statistical inference. These adjustments, known for many years, are used routinely by some health researchers but not by others. We review some of these methods and give an example of their use in a health services study for a continuous and a count outcome. For the continuous outcome, we describe re-transformation using the smear factor, accounting for missing cases via multiple imputation and attrition weights and improving results with bootstrap methods. For the count outcome, we describe zero inflated Poisson and negative binomial models and the two-part model to account for overabundance of zero values. Recent advances in computing and software development have produced user-friendly computer programs that enable the data analyst to improve prediction and inference based on regression analysis.

Data Interpretation, Statistical↗