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Results for “Logistic Model”

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PubMed2007

A logistic model for the prediction of the influence of water on the solid waste methanization in landfills.

This article deals with the impact of water content of solid waste on biogas production kinetics in landfills. This impact has been proved in the laboratory thanks to anaerobic biodegradation experiments on paper/cardboard waste samples. A strong dependence with the moisture level was observed for both kinetic rates and maximum methane production. In this article, a logistic model is proposed to simulate the biogas production rate. It is chosen as simple as possible in order to allow for a correct identification of the model parameters given the experimental data available. The moisture dependency is introduced through a linear weighing of the biomass specific growth rate and of the amount of accessible organic substrate. It is directly linked to physical properties of the waste: the holding capacity and the minimal moisture level allowing the presence of free water.

Bacteria, Anaerobic↗

PubMed1997

A logistic model for trend in 2 x 2 x kappa tables with applications to meta-analyses.

There recently has been an increased interest in examining the relationship between the baseline (control) risk of an adverse outcome and the magnitude of the treatment effect (Brand and Kragt, 1992, Statistics in Medicine 11, 2077-2082; Davey Smith, Song, and Sheldon, 1993, The British Medical Journal 306, 1367-1373; Senn, 1994, Statistics in Medicine 13, 293-294). To facilitate such an examination, we propose a logistic model in which the relationship between the treatment effect, as measured by the log odds ratio, and the baseline risk is specified parametrically. This procedure is founded on a product-binomial likelihood and generates maximum likelihood estimates of the baseline event rates and two parameters characterizing the trend in the treatment effect. We fit this model to data from a meta-analysis involving the treatment of women at risk of preterm labor and contrast our findings with those of an earlier analysis.

Biometry↗

PubMed1986

Choosing near-linear parameters in the four-parameter logistic model for radioligand and related assays.

Ten parameters extracted from six currently used parametrizations of the four-parameter logistic model, and one new proposal, were examined for their statistical behavior in nonlinear least-squares estimation in combination with ELISA and RIA data. Those which are adequately near-linear on the basis of the Lowry-Morton lambda statistic were identified and can be recommended for use in practice.

Enzyme-Linked Immunosorbent Assay↗

PubMed1999

Pharmacodynamic analysis of analgesic clinical trials: nonlinear mixed-effects logistic models.

In the development of an analgesic product, placebo-controlled clinical trials in patients with defined pain are used to study the dose-time-response relationship of the drug. In such trials, the response is usually an ordered categorical variable with longitudinal and subject-specific repeated measurements. The primary causal variables are time and analgesic concentration. The response may be informative right-hand censored because remedication with a known analgesic may be given if a patient has inadequate pain relief. Mixed-effects logistic models are used to estimate the probabilities of having certain pain relief or pain severity scores. A jackknife method is proposed to estimate the standard errors of parameter estimates. Posterior estimates of these probabilities, or of the scores themselves, allow the evaluation of efficacy for an analgesic. In this evaluation, therapeutic as well as statistical significance is assessed. Two case studies, one focusing on pain relief and the other on pain severity, are used to demonstrate the approach. The level of baseline pain appears to be a determinant of the pattern of response.

Analgesics↗

PubMed2000

Sequential logistic models for 30 days mortality after CABG: pre-operative, intra-operative and post-operative experience--The Israeli CABG study (ISCAB). Three models for early mortality after CABG.

OBJECTIVES: The goal of this paper was to examine the added effect of operative and post-operative variables on 30 days mortality, in addition to patients' case-mix factors. SETTING AND DESIGN: A prospective study of 4835 patients, 95% of all Israeli patients who underwent coronary artery bypass grafting (CABG) in 1994. Information related to risk of death was collected at admission to hospital (preceding the operation), at time of the operation and in the immediate post-operative period. Deaths were independently ascertained. METHOD: Data collectors followed every patient from admission to discharge. Sequential logistic models were constructed for the 'case-mix', 'operative' and the 'post-operative' periods in chronological order. Each model incorporated and adjusted for the risk estimated at the previous point in time, by forcing individual risk scores. RESULTS: Significant pre-operative risk factors for 30 days mortality, in the case-mix model included mainly severity of illness characteristics, such as, left ventricular dysfunction and emergency admission, (c-statistic 78.8%). Model 2 (the 'operation' model) included in addition to the case-mix score, excessive duration of the operation per graft, bleeding, etc. (c-statistic 85.3%). The post-operative model showed the added effect of the post-operative factors such as low haemoglobin, additional surgery, and excessive time on respirator, (c-statistic 92.4%). CONCLUSIONS: The sequential analysis was an efficient method for updating patients' risk over time, where the number of events was small, relative to the number of risk factors. The addition of peri-operative factors increased significantly the predictive power of the model, adding clinical insights to the role of the hospital experience on 30 days mortality.

Adult↗

PubMedDate not supplied

The logistic model for predicting the non-gonoactive Aedes aegypti females.

OBJECTIVE: To estimate, using logistic regression, the likelihood of occurrence of a non-gonoactive Aedes aegypti female, previously fed human blood, with relation to body size and collection method. MATERIAL AND METHODS: This study was conducted in Monterrey, Mexico, between 1994 and 1996. Ten samplings of 60 mosquitoes of Ae. aegypti females were carried out in three dengue endemic areas: six of biting females, two of emerging mosquitoes, and two of indoor resting females. Gravid females, as well as those with blood in the gut were removed. Mosquitoes were taken to the laboratory and engorged on human blood. After 48 hours, ovaries were dissected to register whether they were gonoactive or non-gonoactive. Wing-length in mm was an indicator for body size. The logistic regression model was used to assess the likelihood of non-gonoactivity, as a binary variable, in relation to wing-length and collection method. RESULTS: Of the 600 females, 164 (27%) remained non-gonoactive, with a wing-length range of 1.9-3.2 mm, almost equal to that of all females (1.8-3.3 mm). The logistic regression model showed a significant likelihood of a female remaining non-gonoactive (Y=1). The collection method did not influence the binary response, but there was an inverse relationship between non-gonoactivity and wing-length. CONCLUSIONS: Dengue vector populations from Monterrey, Mexico display a wide-range body size. Logistic regression was a useful tool to estimate the likelihood for an engorged female to remain non-gonoactive. The necessity for a second blood meal is present in any female, but small mosquitoes are more likely to bite again within a 2-day interval, in order to attain egg maturation. The English version of this paper is available too at: http://www.insp.mx/salud/index.html.

Aedes↗

PubMed1997

Regressive logistic modeling of familial aggregation for asthma in 7,394 population-based nuclear families.

The aim of this population-based study was to determine whether asthma aggregates in families, and if so, whether aggregation was consistent with environmental and/or genetic etiologies. Data were from 7,394 nuclear families (41,506 individuals) from the 1968 Tasmanian Asthma Survey, in which all Tasmanian schoolchildren born in 1961 were surveyed by respiratory questionnaire completed by their parents. Similar data were obtained for parents and siblings of probands. For a child, having ever had asthma was predicted by a parent or sibling having ever had asthma; odds ratio (OR) = 3.13 (95% confidence interval [CI] 2.82-3.48) for mother, 2.99 (2.69-3.32) for father, and 3.47 (3.23-3.72) for a sibling. Regressive logistic modeling showed that, in addition to parent-offspring effects, the data were consistent with the existence of an unmeasured factor shared by siblings, evident in 15% (SE 2%) of families and associated with a conditional OR of 9.68 (8.27-11.32). Familial aggregation was best described by a general oligogenic model with non-Mendelian transmission probabilities. Of the Mendelian models, a codominant model with an allele frequency of 16% (SE 0.3%) was preferred. Under a dominant model there was evidence for additional parent-offspring and sibling effects of similar magnitude. It is unlikely that there is one major loci influencing asthma susceptibility; the overall effects of asthma genes in the population are more likely to be inherited codominantly, at least for the majority of loci of major etiological importance. The role of environmental factors in explaining part of familial aggregation for asthma cannot be ruled out, as major triggers of asthma attacks are familial.

Asthma↗

PubMed1991

Logistic models describing effects of temperature and humidity on residual effectiveness of chlorpyrifos and cyfluthrin formulations against German cockroaches (Dictyoptera: Blattellidae).

Multifactored logistic models were developed for chlorpyrifos and cyfluthrin formulations based on mortality data from laboratory studies with the German cockroach, Blattella germanica (L.). Insecticides were applied to stainless steel surfaces and aged at three different temperatures (23, 30, and 37 degrees C) and two levels of relative humidity (40 and 70%). After the insecticides dried, the treated panels were placed opposite plywood panels to simulate a crack and crevice application. At appropriate aging times, treated panels were removed from environmental chambers for bioassay. The combined effects of high temperature, high humidity, and aging of residues caused the greatest decline in cockroach mortality for chlorpyrifos. Increasing temperature and aging of residues resulted in decreased cockroach mortality for cyfluthrin formulations; however, mortality was greater than 87% for all formulations through 84 d. Information from this study can be incorporated into integrated pest management programs for German cockroaches.

Animals↗

PubMed2003

Causal logistic models for non-compliance under randomized treatment with univariate binary response.

We propose a method for estimating the marginal causal log-odds ratio for binary outcomes under treatment non-compliance in placebo-randomized trials. This estimation method is a marginal alternative to the causal logistic approach by Nagelkerke et al. (2000) that conditions on partially unknown compliance (that is, adherence to treatment) status, and also differs from previous approaches that estimate risk differences or ratios in subgroups defined by compliance status. The marginal causal method proposed in this paper is based on an extension of Robins' G-estimation approach for fitting linear or log-linear structural nested models to a logistic model. Comparing the marginal and conditional causal log-odds ratio estimates provides a way of assessing the magnitude of unmeasured confounding of the treatment effect due to treatment non-adherence. More specifically, we show through simulations that under weak confounding, the conditional and marginal procedures yield similar estimates, whereas under stronger confounding, they behave differently in terms of bias and confidence interval coverage. The parametric structures that represent such confounding are not identifiable. Hence, the proof of consistency of causal estimators and corresponding simulations are based on two different models that fully identify the causal effects being estimated. These models differ in the way that compliance is related to potential outcomes, and thus differ in the way that the causal effect is identified. The simulations also show that the proposed marginal causal estimation approach performs well in terms of bias under the different levels of confounding due to non-adherence and under different causal logistic models. We also provide results from the analyses of two data sets further showing how a comparison of the marginal and conditional estimators can help evaluate the magnitude of confounding due to non-adherence.

Confounding Factors, Epidemiologic↗

PubMed1987

Use of simultaneous curve fitting and a four-parameter logistic model to evaluate the nutritional quality of protein sources at growth rates of rats from maintenance to maximum gain.

A four-parameter logistic model was used to describe the dose-response relationship of rats fed diets containing 12 levels of casein, peanut meal or wheat gluten. The model was capable of accurately describing the entire response curve of rats fed diets containing each of the three protein sources. Incorporation of a technique known as parameter sharing into the curve-fitting process facilitated convergence of the parameter estimates for b (the response of rats fed a protein-free diet) and Rmax (maximum response) for all curves when compared with the values observed experimentally. Parameter sharing also provided a method by which the curves could be differentiated on a statistical basis. These data indicate that the relative value of a protein source is dependent on the concentration of the protein in the diet. The application of nonlinear models combined with parameter sharing provides a technique by which protein values can be evaluated at levels of animal response from maintenance to maximum growth.

Animals↗

PubMed1998

Gibbs sampler for the logistic model in the analysis of longitudinal binary data.

Logistic mixed-effects models constitute a natural framework to study longitudinal binary response variables when the question addressed with the data is related to covariate effects within persons. However, the computations of the likelihoods are generally tedious and require the resolution of integrals which have no analytical solution. In this paper, we study a logistic mixed-effects model in a Bayesian framework and use the Gibbs sampler to overcome the current computational limitations. From a study of side-effects occurring during plasma exchanges, we explore the issues of bayesian formulation, model parametrization, choice of the prior distributions, diagnosing convergence, comparison between models and model adequacy. Finally, we show that a Bayesian random-effects model is useful to facilitate prediction.

Bayes Theorem↗

PubMed1995

Multiple estimation of concentrations in immunoassay using logistic models.

Immunoassay techniques yield estimates of concentrations of analytes based on comparison to known concentrations of a reference solution. The use of the nonlinear logistic model makes the error estimates and confidence levels approximate. When the goal of such a study is estimation of several unknowns, methods in common usage do not account for 'simultaneous' inference, i.e. the repeated use of the standard curve for estimating several concentrations. Alternative methods are described which take multiple use of the reference curve into account. Simulations using normally distributed data with variance proportional to a power of the mean compare different methods of obtaining calibration intervals and illustrate the approximate nature of all such techniques. Calibration intervals based on simple, commonly used methods do not provide the coverage promised, even for one-at-a-time estimation, and are not suited for multiple estimation and comparison.

Analysis of Variance↗

PubMed1998

A multivariate logistic model (MLM) for analyzing binary family data.

We consider modeling the familial correlation between 2 related individuals using a multiple logistic regressive model. It is shown that there is a discrepancy in the marginal probability of the second individual. We investigate the conditions under which this discrepancy can be minimized and show how it can have a direct effect on handling missing values and ascertainment. We derive a functional relationship between the parameters in the model that eliminates this discrepancy, hence solving the problems that can arise in the handling of missing values and ascertainment. Because this methodology fails when there are more than 2 related individuals, we present a new model based on a multivariate logistic distribution. Residual familial correlations can be directly related to the parameters of this model. The likelihood for family data under this model is independent of the order in which the family members enter the calculation. The marginal probabilities can be easily computed.

Data Interpretation, Statistical↗

PubMed1985

The use of a logistic model for the quantitative interpretation of indirect sandwich enzyme labelled immunosorbent assays (ELISA) for antibodies and antigens in foot and mouth disease.

A three parameter logistic model is described for the analysis of profiles of optical density vs log dose for indirect sandwich ELISA tests in foot and mouth disease. The model describes the observed phenomenon of saturability with increasing dose, and its parameters can be interpreted in terms of molecular binding events. A computer program to fit the model is described. An approximate statistical test is developed which can be used to test for departures from equivalence for replicate profiles. It is found that correlation of the optical density values to a standard reference reaction considerably improves reproducibility.

Animals↗

PubMed1985

Survival probabilities of infants delivered prior to the 34th week of pregnancy as estimated by means of a logistic model.

Survival of 188 infants born alive before the 34th wk of pregnancy is assessed in relation both to birthweight and duration of pregnancy. A logistic model is used which describes, based on these parameters, probabilities of 1-yr survival of relatively small populations in a continuous way. Although there may be differences between measured and estimated birthweight, this method might enable the perinatologist to estimate before birth the survival probabilities if he knows the duration of pregnancy and estimated birthweight.

Birth Weight↗

PubMed1990

Detection of restenosis after successful coronary angioplasty: improved clinical decision making with use of a logistic model combining procedural and follow-up variables.

A prospective study of 111 patients who underwent repeat coronary angiography and exercise thallium-201 scintigraphy 6 +/- 2 months after complete revascularization by percutaneous transluminal coronary angioplasty was performed to assess whether clinical, procedure-related and postangioplasty exercise variables yield independent information for the prediction of angiographic restenosis after angioplasty. Complete revascularization was defined as successful angioplasty of one or more vessels that resulted in no residual coronary lesion with greater than 50% diameter stenosis. Restenosis was defined as a residual stenosis at the time of repeat angiography of greater than 50% of luminal diameter. Restenosis occurred in 40% of the patients. The 111 patients were randomly subdivided into a learning group (n = 84) and a testing group (n = 27). A logistic discriminant analysis was performed in the learning group and the logistic model was used to estimate a logistic probability of restenosis. This probability of restenosis was validated in the testing group. In the learning group of 84 patients univariate analysis of 39 factors revealed 8 factors related to restenosis: recurrence of angina (p less than 0.0001), postangioplasty abnormal finding on exercise thallium-201 scintigram (p less than 0.0001), exercise thallium-201 scintigram score (p less than 0.0001), difference between exercise and rest ST segment depression (p less than 0.001), postangioplasty exercise ST segment depression (p less than 0.001), absolute postangioplasty stenosis diameter (p less than 0.003), postangioplasty exercise work load (p less than 0.03) and postangioplasty exercise heart rate (p less than 0.05).(ABSTRACT TRUNCATED AT 250 WORDS)

Angina Pectoris↗

PubMed1994

Extension of the four-parameter logistic model for ELISA to multianalyte analysis.

The standard implementation of enzyme-linked immunosorbent assay (ELISA) for single analytes can lead to false conclusions if cross reacting compounds are present in the sample. This paper discusses the extension of the usual four-parameter logistic model for ELISA to the case of multiple cross-reacting analytes. The use of the extended model in multianalyte analysis (MELISA) is illustrated and compared with a more simplistic approach. Data on the analysis of a binary mixture of s-triazines suggests the superiority of the proposed model. This model is also suitable for other forms of immunoassay that use the four-parameter logistic curve.

Cross Reactions↗

PubMedDate not supplied

On the use of the logistic model in prospective studies.

We describe the usual statistical concepts and consequent appropriate simulations of a prospective study for the simple case of a single risk variable and an assumed logistic model. We examine the simulations of Lilienfeld and Pyne, and show that they are seriously flawed. Contrary to those authors' claims, the estimates of parameters by the Walker-Duncan technique are both accurate and reliable.

Biometry↗