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Results for “Logistic Model”

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PubMed1999

Effects of immigration on some stochastic logistic models: a cumulant truncation analysis.

This paper uses a new cumulant truncation methodology to investigate the stochastic power law logistic model with immigration, and illustrates the model with parameter values used to describe the growth of muskrat populations in the Netherlands. This model has a stable equilibrium distribution. The incorporation of immigration into the model, therefore, simplifies the qualitative nature of the stochastic solution. The (unconditional) cumulant functions for the transient and the equilibrium population size distributions are obtained, from which the distributions are shown to be near-normal at all times for the parameter values of interest. Approximating cumulant functions, which are relatively easy to find in practice, are derived and shown to be quite accurate, except for the case of massive immigration. As the level of immigration increases, the mean value rises more rapidly initially, as expected; however, the variance and the skewness of both the transient and the equilibrium distributions are reduced.

Animals↗

PubMed1990

Incorporation of twins in the regressive logistic model for pedigree disease data.

Segregation and twin disease concordance analyses have assumed a theoretical underlying liability following a multivariate normal distribution. For reasons of computation, of incorporation of measured explanatory variables, and of testing of fit and assumptions, newer analytical methods are being developed. The regressive logistic model (RLM) relies on expressing the pedigree likelihood as a product of conditional probabilities, one for each individual. In addition to logistic regression modelling of measured epidemiological variables on disease prevalence, there is modelling of vertical transmission, of transmission of unmeasured genotypes and of sibship environment. This paper discusses methods for the analysis of binary traits in twins and in pedigrees. Some extensions to the RLM for pedigrees which include twins are proposed. These enable exploration of twin concordance in the context of the twins' common parenthood, the sibship similarities within the family, and the twins' similarity in age, sex, genes and environment.

Asthma↗

PubMed2005

Predicting risk-adjusted mortality for CABG surgery: logistic versus hierarchical logistic models.

BACKGROUND: In recent years, several studies in the medical and health service research literature have advocated the use of hierarchical statistical models (multilevel models or random-effects models) to analyze data that are nested (eg, patients nested within hospitals). However, these models are computer-intensive and complicated to perform. There is virtually nothing in the literature that compares the results of standard logistic regression to those of hierarchical logistic models in predicting future provider performance. OBJECTIVE: We sought to compare the ability of standard logistic regression relative to hierarchical modeling in predicting risk-adjusted hospital mortality rates for coronary artery bypass graft (CABG) surgery in New York State. DESIGN, SETTING AND PATIENTS: New York State CABG Registry data from 1994 to 1999 were used to relate statistical predictions from a given year to hospital performance 2 years hence. MAIN OUTCOME MEASURES: Predicted and observed hospital mortality rates 2 years hence were compared using root mean square errors, the mean absolute difference, and the number of hospitals whose predicted mortality rate data was within a 95% confidence interval around the observed mortality rate. RESULTS: In these data, standard logistic regression performed similarly to hierarchical models, both with and without a second level covariate. Differences in the criteria used for comparison were minimal, and when the differences could be statistically tested no significant differences were identified. CONCLUSIONS: It is instructive to compare the predictive abilities of alternative statistical models in the process of assessing their relative performance on a specific database and application.

Coronary Artery Bypass↗

PubMed1992

A logistic model for thyroid lesions.

A stepwise logistic regression analysis was performed in 27 cases of papillary carcinoma thyroid (PC), 20 follicular neoplasms (FN), 30 cases of Grave's disease (GD), and 40 cases of colloid adenomatous goitre (CAG). The three most important variables in predicting PC were papillary clusters, dense cytoplasm, and intranuclear cytoplasmic inclusions, whereas the predictors of FN were high cellularity combined with a prominent acinar pattern. A few cases of GD and CAG showed a cytologic overlap with PC and FN, respectively. Regression analysis established high cellularity, fire flare appearance, and epitheloid granulomas as reliable predictors of GD, whereas abundant colloid with or without foam cells and follicles associated with colloid (FAC) were important variables in CAG.

Adenocarcinoma↗

PubMed2002

Simulation of rice biomass accumulation by an extended logistic model including influence of meteorological factors.

The biomass (X) of a biological population, described by growth models, depends only on time (t), i.e., X = f(t). Some parameters in these models are frequently taken as constants, but they may vary with growth processes under different ecological conditions. An extended logistic model including changes in the influence of meteorological factors is developed to simulate biomass accumulation processes of rice sown on different dates. The model may be generally described as X = f (p, t), in which p stands for meteorological factors. The model can be used to generalize population growth processes in experiments carried out under different environments. It is shown that the model may account for 96.6% of the variance of rice biomass on the basis of sowing dates, developmental stage, solar radiation and temperature in the Yangtze River valley in China.

Biomass↗

PubMed1989

Familial analysis of bipolar affective disorder using logistic models.

Data on bipolar affective disorder in 187 pedigrees from the Collaborative Depression Study were analyzed using logistic models that have been extended to incorporate age of onset information. Logistic regression analysis and segregation analysis revealed evidence for complex familial effects on this disorder.

Age Factors↗

PubMed2006

Modeling crash outcome probabilities at rural intersections: application of hierarchical binomial logistic models.

It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

Accidents, Traffic↗

PubMed2002

Prediction of early and delayed postoperative deaths after coronary artery bypass surgery alone in Italy. Multivariate predictions based on Cox and logistic models and a chart based on the accelerated failure time model.

BACKGROUND: The aim of the multicenter OP-RISK (OPerative RISK) study was to investigate the early (28 days) and delayed (365 days) death rates following coronary artery bypass grafting (CABG) among patients representing a nationwide distribution [Centers in Northern (2), Central (1) and Southern (1) Italy] and further to define the multivariate risk factors for the early and delayed mortality after CABG. METHODS: Data were collected from 1126 patients undergoing CABG alone. Data were analyzed using Cox and logistic regression models, to accurately assess the major factors influencing survival over time after CABG. Having defined the significant factors, we constructed a chart of the absolute early risk of mortality using the accelerated failure time model. RESULTS: Using the Cox proportional hazards model and logistic regression we have demonstrated that age, preoperative ejection fraction and heart rate, and the duration of aortic cross-clamping are multivariate risk factors in the short and long term. The role of one arterial conduit was also assessed. CONCLUSIONS: The OP-RISK study produced relevant information for risk assessment and control in CABG and the results may form the basis for the objective quality assurance and accreditation of cardiac surgical institutions in Italy. Incidentally, Cox model appeared more adequate than logistic model for the assessment of the major factors influencing survival over time after CABG. The risk factors so assessed were used to construct a chart for practical predictive purposes.

Adult↗

PubMed1990

[A program for analysis of dose-response relationship with logistic model].

In order to avoid the defects in common methods for analysis of dose-response curves, we fit groups of dose-response curves simultaneously or separately on computer by using logistic model, with the EC50 and slope factor as the basic parameters. The pD2 and pA2 values were calculated from the best estimated EC50s. This method shows a good compatibility with the original experimental data. The BASIC program can be conveniently run on microcomputers.

Animals↗

PubMed1996

Using a logistic model to identify women with first-trimester spontaneous abortion suitable for expectant management.

OBJECTIVE: To design a method to identify women with first trimester spontaneous abortion suitable for expectant management. DESIGN: A stepwise logistic regression analysis based on retrospective analysis of clinical and biochemical variables. SETTING: Department of Obstetrics and Gynaecology, Sahlgrenska University Hospital, Gothenburg, Sweden. PARTICIPANTS: One hundred and three women with inevitable or incomplete spontaneous abortion at < 13 weeks of gestation were chosen for expectant management. Eighty-one women with complete spontaneous abortion (i.e. complete expulsion and/or resolution of pregnancy products within three days of expectant management) were compared with those (n = 22) who underwent surgical evacuation of the uterus, most commonly owing to retained products of conception after three days. RESULTS: Employing a stepwise logistic regression procedure, five diagnostic variables possessing prognostic power were identified: serum progesterone, daily serum hCG change, serum CA125, serum alpha fetoprotein and intrauterine diameter. The logistic regression analysis was also applied to three diagnostic variables chosen for routine clinical use: serum progesterone, serum hCG and intrauterine diameter. The probability of complete spontaneous abortion within three days of expectant management in each woman could be calculated. CONCLUSION: We have used a logistic model to calculate the probability of complete spontaneous abortion within three days in women with first trimester miscarriages. Such information may be of clinical use in caring for women, as well as for development of management guidelines for those with miscarriages.

Abortion, Spontaneous↗

PubMed2005

Genetic parameters of claw and foot disorders estimated with logistic models.

The primary aim of this study was to estimate heritabilities for different types of claw and foot disorders and the genetic relationship of disorders with milk yield and selected conformation traits by applying logistic models in Holstein dairy cattle. The study included data from 5634 Holstein cows kept on large-scale dairy farms in Eastern Germany. Dichotomous response variables were the presence or absence of the disorder in 2003. Cows that were present in herds for <6 wk in 2003 were excluded from the analysis. Incidences, disregarding repeated measurements, for digital dermatitis (DD), sole ulceration (SU), wall disorder (WD), and interdigital hyperplasia (IH) in rear legs were 13.2, 16.1, 9.6, and 6.3%, respectively. The herd effect was highly significant for all disorders. Incidences increased with increasing parities for SU and WD, but were highest among heifers for DD. High milk yield at the first 2 test d after calving was associated with a greater risk for claw and foot disorders in the same lactation. Estimates of heritability were 0.073 for DD, 0.086 for SU, 0.104 for WD, and 0.115 for IH. Genetically, health problems appear to occur in clusters (i.e., a cow showing one disease has an increased genetic risk of showing another claw disease). This phenomenon was also observed between claw and foot disorders and the somatic cell score. Genetic correlations between milk yield in early lactation and disorders were 0.240 for DD, 0.057 for SU, 0.270 for WD, and 0.336 for IH, indicating a physiological antagonism. Correlations between breeding values for claw and foot disorders of bulls and official breeding values for functional type traits were mostly favorable. Routine recording of claw data will offer a new chance to improve claw health within the population as was elaborated by different scenarios applying selection index procedures.

Animals↗

PubMed1997

Tree-structured logistic models for over-dispersed binomial data with application to modeling developmental effects.

This article proposes tree-structured logistic regression modeling for over-dispersed binomial data. Recursive partitioning is performed using a combination of statistical tests and residual analysis. The splitting criterion in cross-validation is based on the deviance function. A nested grid algorithm to estimate the bootstrap parameters is developed. The regression tree procedure provides a new approach for exploring in detail the relationship between the binomial response and explanatory variables. The proposed procedure is used to model the relationship between the incidence of malformation and dose and fetal weight using data from a developmental experiment conducted at the National Center for Toxicological Research. A conditional Gaussian chain model is used to account for the effect of fetal weight by dose.

2,4,5-Trichlorophenoxyacetic Acid↗

PubMed2006

Comparing the predictive value of neural network models to logistic regression models on the risk of death for small-cell lung cancer patients.

Cancer is one of the leading causes of mortality in the developed world, and prognostic assessment of cancer patients is indispensable in medical care. Medical researchers are accustomed to using regression models to predict patient outcomes. Neural networks have been proposed as an alternative with great potential. Nonetheless, empirical evidence remains lacking to support the application of this technique as the appropriate method to investigate cancer prognosis. Utilizing data on patients from two National Cancer Institute of Canada clinical trials, we compared predictive accuracy of neural network models and logistic regression models on risk of death of limited-stage small-cell lung cancer patients. Our results suggest that neural network and logistic regression models have similar predictive accuracy. The distributions of individual predicted probabilities are very similar. On occasion, however, the prediction pairs are quite different, suggesting that they do not always give the same interpretations of the same variables.

Adult↗

PubMed1994

[Multivariate analysis on prognostic factors for acute myocardial infarction during acute period noncondition stepwise logistic model].

The relationship between baseline factors defined at 4.3 +/- 1.8 hr after onset of acute myocardial infarction and 28-day survival in 319 patients admitted into the China Medical University was evaluated. The case fatality rate during acute period was 17.9%. Univariate statistics identified a significant relationship between 5 of these factors and survival. Multivariate noncondition stepwise logistic model analysis identified four factors as being most closely related to survival: (1) heart failure; (2) arrhythmia; (3) age; (4) history of essential hypertension. It is concluded that heart failure during the acute period of acute myocardial infarction is the most important baseline factor for prediction of 28-day survival.

Aged↗

PubMed2006

Growth characteristics of pearl gray guinea fowl as predicted by the Richards, Gompertz, and logistic models.

This study was undertaken to describe the growth pattern of the pearl gray Guinea fowl. Using BW data from hatch to 22 wk, 3 nonlinear mathematical functions (Richards, Gompertz, and logistic) were used to estimate growth patterns of the pearl gray guinea fowl. The logistic and Gompertz models are a special case of the Richards model, which has a variable point of inflection defined by the shape or growth trajectory parameter, m. The shape parameter m was 1.08 and 0.98 in males and females, respectively, suggesting that the growth pattern of the pearl gray female guinea fowl is Gompertz. The pearl gray guinea fowl exhibited sexual dimorphism for their growth characteristics. From the Gompertz model, the asymptotic BW, growth rate, and age at maximum growth were 1.62 kg, 0.22 kg/wk, and 6.65 wk in males, respectively, and 1.70 kg, 0.19 kg/wk, and 6.70 wk in females, respectively. The ages at maximum growth were 6.65, 6.47, and 8.12 wk for the Richards, Gompertz, and logistic models, respectively. The pearl gray guinea fowl females have a higher asymptotic BW compared with the males. The average asymptotic BW of about 1.57 kg for both sexes predicted by the logistic model was below the average predicted BW from the Richards (1.66 kg) and Gompertz (1.67 kg) models, respectively, at 22 wk of age. The inverse relationship between the asymptotic weight and both relative growth and age at maximum growth of the pearl gray guinea fowl is similar to that of chickens, quail, and ducks. Success in studying the growth characteristics of guinea fowl will contribute to the efforts of genetically improving this least-studied avian species.

Aging↗

PubMedDate not supplied

Exercise testing in patients with chest pain and normal coronary arteries: improving test specificity by use of a simple logistic model.

Despite an exercise electrocardiogram (ECG) positive for ischemia by established criteria, many patients referred for coronary angiography to evaluate chest pain are found to have angiographically normal coronary arteries (NCA). Exercise ECG were analyzed from 27 patients with chest pain and angiographically NCA and 28 patients with chest pain and coronary artery disease (CAD) using univariate and multivariate logistic regression analysis. We derived the following logistic model for the logit probability of CAD: 3 + SEX x 4 - METs x 0.7 + STDV5 x 0.8, where SEX = 0 for female and SEX = 1 for male, METs = maximal estimated work load (metabolic equivalents) and STDV5 = horizontal or downsloping ST depression (mm) in V5. A logit probability > or = 0 identified CAD with a sensitivity of 79% and a specificity of 89%. The model correctly identified 28/36 (78%) patients with CAD, and 7/10 (70%) patients with NCA (correct diagnosis 76%; p < 0.02) in a separate random group of 46 unselected patients with positive exercise tests undergoing diagnostic coronary angiography.

Adult↗

PubMed1994

Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies.

This article describes how genetic components of disease susceptibility can be evaluated in case-control studies, where cases and controls are sampled independently from the population at large. Subjects are assumed unrelated, in contrast to studies of familial aggregation and linkage. The logistic model can be used to test collapsibility over phenotypes or genotypes, and to estimate interactions between environmental and genetic factors. Such interactions provide an example of a context where non-hierarchical models make sense biologically. Also, if the exposure and genetic categories occur independently and the disease is rare, then analyses based only on cases are valid, and offer better precision for estimating gene-environment interactions than those based on the full data.

Biomarkers↗

PubMed1994

Ovarian tumors: prediction of the probability of malignancy by using patient's age and tumor morphologic features with a logistic model.

An attempt was made to predict the probability of malignancy of a given ovarian tumor in a certain patient by using the age and simple morphologic features of the tumor. A cohort of 959 patients with ovarian tumors was analysed retrospectively according to the patient's age and tumor characteristics such as greatest diameter, consistency, bilaterality and diagnosis as malignant (271 patients) or benign (688 patients). All variables were entered unconditionally in a logistic regression. The presence of solid/multilocular elements has a 9.6-fold increased risk of malignancy, where a bilateral tumor has a 2.8-fold increase. Significant increase in risk of malignancy was observed in ages under 20 and over 40 years, as well as in tumors with a diameter larger than 9 cm. All variables were highly significant associated with the discrimination between benign and malignant. A formula including all variables has been developed so that the probability of malignancy can be estimated by a scientific calculator. In conclusion, simple, easily determined by ultrasound and reproducible criteria such as patient's age, tumor size, consistency and bilaterality were assembled in a logistic model in order to predict the probability of malignancy for a given ovarian tumor, in an individual patient.

Adult↗