LOGITCPRPLOT: Stata module to graph component-plus-residual plot for logistic regression

logitcprplot can be used after logistic regression for graphing a component-plus-residual plot (a.k.a. partial residual plot) for a given predictor, including a lowess, local polynomial, restricted cubic spline, fractional polynomial, penalized spline, regression spline, running line, or adaptive variable span running line smooth

RRLOGIT: Stata module to estimate logistic regression for randomized response data

rrlogit fits a maximum-likelihood logistic regression for randomized response data.

A review of two journals found that articles using multivariable logistic regression frequently did not report commonly recommended assumptions

Background and Objective: To examine if commonly recommended assumptions for multivariable logistic regression are addressed in two major epidemiological journals. Methods: Ninety-nine articles from the Journal of Clinical Epidemiology and the American Journal of Epidemiology were surveyed for 10 criteria: six dealing with computation and four with reporting multivariable logistic regression results. Results: Three of the 10 criteria were addressed in 50% or more of the articles. Statistical significance testing or confidence intervals were reported in all articles. Methods for selecting independent variables were described in 82%, and specific procedures used to generate the models were discussed in 65%. Fewer than 50% of the articles indicated if interactions were tested or met the recommended events per independent variable ratio of 10: 1. Fewer than 20% of the articles described conformity to a linear gradient, examined collinearity, reported information on validation procedures, goodness-of-fit, discrimination statistics, or provided complete information on variable coding. There was no significant difference (P >.05) in the proportion of articles meeting the criteria across the two journals. Conclusion: Articles reviewed frequently did not report commonly recommended assumptions for using multivariable logistic regression. (C) 2004 Elsevier Inc. All rights reserved.

Optimal crossover designs for logistic regression models in pharmacodynamics

Pharmacodynamics (PD) is the study of the biochemical and physiological effects of drugs. The construction of optimal designs for dose-ranging trials with multiple periods is considered in this paper, where the outcome of the trial (the effect of the drug) is considered to be a binary response: the success or failure of a drug to bring about a particular change in the subject after a given amount of time. The carryover effect of each dose from one period to the next is assumed to be proportional to the direct effect. It is shown for a logistic regression model that the efficiency of optimal parallel (single-period) or crossover (two-period) design is substantially greater than a balanced design. The optimal designs are also shown to be robust to misspecification of the value of the parameters. Finally, the parallel and crossover designs are combined to provide the experimenter with greater flexibility.

Modeling Data for Complications in Diabetics Using Logistic Regression

2010 Mathematics Subject Classification: 62P10.

Sequential Logistic Regression: A Method to Reveal Subtlety in Self-Efficacy

This paper uses self-efficacy to predict the success of women in introductory physics. We show how sequential logistic regression demonstrates the predictive ability of self-efficacy, and reveals variations with type of physics course. Also discussed are the sources of self-efficacy that have the largest impact on predictive ability.

Use of posterior predictive assessments to evaluate model fit in multilevel logistic regression

Assessing the fit of a model is an important final step in any statistical analysis, but this is not straightforward when complex discrete response models are used. Cross validation and posterior predictions have been suggested as methods to aid model criticism. In this paper a comparison is made between four methods of model predictive assessment in the context of a three level logistic regression model for clinical mastitis in dairy cattle; cross validation, a prediction using the full posterior predictive distribution and two “mixed” predictive methods that incorporate higher level random effects simulated from the underlying model distribution. Cross validation is considered a gold standard method but is computationally intensive and thus a comparison is made between posterior predictive assessments and cross validation. The analyses revealed that mixed prediction methods produced results close to cross validation whilst the full posterior predictive assessment gave predictions that were over-optimistic (closer to the observed disease rates) compared with cross validation. A mixed prediction method that simulated random effects from both higher levels was best at identifying the outlying level two (farm-year) units of interest. It is concluded that this mixed prediction method, simulating random effects from both higher levels, is straightforward and may be of value in model criticism of multilevel logistic regression, a technique commonly used for animal health data with a hierarchical structure.

Obtaining environmental favourability functions from logistic regression

Logistic regression is a statistical tool widely used for predicting species’ potential distributions starting from presence/absence data and a set of independent variables. However, logistic regression equations compute probability values based not only on the values of the predictor variables but also on the relative proportion of presences and absences in the dataset, which does not adequately describe the environmental favourability for or against species presence. A few strategies have been used to circumvent this, but they usually imply an alteration of the original data or the discarding of potentially valuable information. We propose a way to obtain from logistic regression an environmental favourability function whose results are not affected by an uneven proportion of presences and absences. We tested the method on the distribution of virtual species in an imaginary territory. The favourability models yielded similar values regardless of the variation in the presence/absence ratio. We also illustrate with the example of the Pyrenean desman’s (Galemys pyrenaicus) distribution in Spain. The favourability model yielded more realistic potential distribution maps than the logistic regression model. Favourability values can be regarded as the degree of membership of the fuzzy set of sites whose environmental conditions are favourable to the species, which enables applying the rules of fuzzy logic to distribution modelling. They also allow for direct comparisons between models for species with different presence/absence ratios in the study area. This makes themmore useful to estimate the conservation value of areas, to design ecological corridors, or to select appropriate areas for species reintroductions.

Exploring Iris Colour Prediction And Ancestry Inference In Admixed Populations Of South America.

New DNA-based predictive tests for physical characteristics and inference of ancestry are highly informative tools that are being increasingly used in forensic genetic analysis. Two eye colour prediction models: a Bayesian classifier - Snipper and a multinomial logistic regression (MLR) system for the Irisplex assay, have been described for the analysis of unadmixed European populations. Since multiple SNPs in combination contribute in varying degrees to eye colour predictability in Europeans, it is likely that these predictive tests will perform in different ways amongst admixed populations that have European co-ancestry, compared to unadmixed Europeans. In this study we examined 99 individuals from two admixed South American populations comparing eye colour versus ancestry in order to reveal a direct correlation of light eye colour phenotypes with European co-ancestry in admixed individuals. Additionally, eye colour prediction following six prediction models, using varying numbers of SNPs and based on Snipper and MLR, were applied to the study populations. Furthermore, patterns of eye colour prediction have been inferred for a set of publicly available admixed and globally distributed populations from the HGDP-CEPH panel and 1000 Genomes databases with a special emphasis on admixed American populations similar to those of the study samples.

Eventos de vida produtores de estresse e queixas de insônia entre auxiliares de enfermagem de um hospital universitário no Rio de Janeiro: estudo Pró-Saúde

OBJETIVO: Avaliar a associação entre eventos de vida produtores de estresse (EVPE) e queixas de insônia (QI). MÉTODOS: Foram analisados dados seccionais de 695 auxiliares de enfermagem de um hospital universitário, participantes do Estudo Pró-Saúde - coorte de funcionários de uma universidade no Rio de Janeiro. As informações foram obtidas através de um questionário multidimensional e autopreenchido, que avaliou a ocorrência de EVPE nos últimos 12 meses, variáveis socioeconômicas e demográficas e QI. As QI foram analisadas como desfecho politômico (frequente, ocasional, e ausente). Odds ratios brutos e ajustados foram calculados através de regressão logística multinomial. RESULTADOS: A prevalência total de QI foi de 45,8% (16,7% frequentes e 29,1% ocasionais). Após ajuste por sexo, idade, estado civil, renda familiar per capita e regime de trabalho, os EVPE associados com QI frequentes foram: "rompimento de relação amorosa" (OR = 3,32; IC95% 1,90 - 5,78), "ter tido problemas graves de saúde" (OR = 2,82; IC95% 1,73 - 4,58); "dificuldades financeiras graves" (OR = 2,38; IC95% 1,46 - 3,88), e "mudança forçada de moradia" (OR = 1,97; IC95% 1,02 - 3,79). Com relação às QI ocasionais, houve associação apenas com rompimento de relação amorosa (OR = 2,30; IC95% 1,42 - 3,74) e dificuldades financeiras graves (OR = 1,87; IC95% 1,27 - 2,75). CONCLUSÕES: Dada a responsabilidade com vidas humanas que os auxiliares de enfermagem assumem durante seu horário de trabalho, nossos achados podem contribuir para ações mais efetivas, por parte dos serviços de saúde ao trabalhador, para lidar com o estresse nessa categoria

Hepatitis B Infection Is Associated with Asymptomatic Malaria in the Brazilian Amazon

Background: Areas that are endemic for malaria are also highly endemic for hepatitis B virus (HBV) infection. Nevertheless, it is unknown whether HBV infection modifies the clinical presentation of malaria. This study aimed to address this question. Methodology and Findings: An observational study of 636 individuals was performed in Rondonia, western Amazon, Brazil between 2006 and 2007. Active and passive case detections identified Plasmodium infection by field microscopy and nested Polymerase Chain Reaction (PCR). HBV infections were identified by serology and confirmed by real-time PCR. Epidemiological information and plasma cytokine profiles were studied. The data were analyzed using adjusted multinomial logistic regression. Plasmodium-infected individuals with active HBV infection were more likely to be asymptomatic (OR: 120.13, P < 0.0001), present with lower levels of parasitemia and demonstrate a decreased inflammatory cytokine profile. Nevertheless, co-infected individuals presented higher HBV viremia. Plasmodium parasitemia inversely correlated with plasma HBV DNA levels (r=-0.6; P=0.0003). Conclusion: HBV infection diminishes the intensity of malaria infection in individuals from this endemic area. This effect seems related to cytokine balance and control of inflammatory responses. These findings add important insights to the understanding of the factors affecting the clinical outcomes of malaria in endemic regions.

A Model for comparing reduced impact logging with conventional logging for an Eastern Amazonian Forest

Using data from a logging experiment in the eastern Brazilian Amazon region, we develop a matrix growth and yield model that captures the dynamic effects of harvest system choice on forest structure and composition. Multinomial logistic regression is used to estimate the growth transition parameters for a 10-year time step, while a Poisson regression model is used to estimate recruitment parameters. The model is designed to be easily integrated with an economic model of decisionmaking to perform tropical forest policy analysis. The model is used to compare the long-run structure and composition of a stand arising from the choice of implementing either conventional logging techniques or more carefully planned and executed reduced-impact logging (RIL) techniques, contrasted against a baseline projection of an unlogged forest. Results from log and leave scenarios show that a stand logged according to Brazilian management requirements will require well over 120 years to recover its initial commercial volume, regardless of logging technique employed. Implementing RIL, however, accelerates this recovery. Scenarios imposing a 40-year cutting cycle raise the possibility of sustainable harvest volumes, although at significantly lower levels than is implied by current regulations. Meeting current Brazilian forest policy goals may require an increase in the planned total area of permanent production forest or the widespread adoption of silvicultural practices that increase stand recovery and volume accumulation rates after RIL harvests. Published by Elsevier B.V.

Gambling in Brazil Lifetime prevalences and socio-demographic correlates

Gambling has experienced world-wide growth The current study is the first national survey into household gambling conducted in a developing country The sample was a three-stage probabilistic one designed to cover individuals 14 years old or older of both genders and from all regions of the national territory 325 census sectors were visited including rural areas DSM-IV-based instruments were used to assess problem and pathological gambling individuals were asked to estimate their monthly gambling expenditure The lifetime prevalences were pathological gambling 1 0% and problem gambling 1 3% Maximum gambling expenditure corresponded to 5 4% of the household income for social gamblers 16 9% for problem gamblers and 20 0% for pathological gamblers The male female ratio among adults for pathological gambling was 3 2 1 The data suggest the existence of two subgroups of pathological gamblers one younger (33 9 +/- 4 19) and severe (7 or more DSM-IV criteria) another older (47 8 +/- 6 01) and less severe (5-6 criteria) In a multinomial logistic regression problematic gambling was associated with gender age education employment region of origin and living in metropolitan areas The data suggest that feeling active and socially inserted protects against problematic gambling Individuals who are young male unemployed or not currently pursuing further education may be at special risk for severe pathological gambling (C) 2010 Elsevier Ireland Ltd All rights reserved