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Results for “Logistic Models”

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PubMed1998

A logistic regression model including DNA status and morphology of spermatozoa for prediction of fertilization in vitro.

To determine predictive values of routine semen analysis, sperm morphology evaluation using strict criteria and DNA status for in-vitro fertilization (IVF), 66 consecutive couples undergoing IVF in a university hospital IVF programme were prospectively investigated. Semen samples from 66 men were evaluated by routine semen analysis, morphology evaluation using strict criteria and acridine orange staining for determination of DNA status. A new technique is described for acridine orange scoring which consisted of evaluation of two smears per case, with and without heat treatment. Resistance to heat-provoked denaturation was determined by the difference between two evaluations. A logistic regression model was built and receiver operating characteristic curves were constructed to determine the threshold values and to compare diagnostic properties. Morphology evaluation using strict criteria and concentration of progressively motile spermatozoa were found to be the principal parameters determining the sperm fertilizing capacity in vitro. The logistic regression model composed of morphology evaluation using strict criteria and acridine orange score had a powerful diagnostic capability for prediction of fertilization in vitro.

Acridine Orange↗

PubMed2004

[The logistic regression model including interactions between the factor variables demonstrated for the detection of E. coli O157.H7 in artificially contaminated minced beef].

Logistic regression is a powerful tool to analyse data sets with a dichotomous response variable. However, in most situations it is used as a model without interactions between the factor variables. This is done either by presumption or to avoid difficulties in the interpretation of the statistical results. In this article first the model of simple logistic regression without interactions is introduced followed by the expanded model with pairwise interactions between the factors. The application of both models is demonstrated at the present data set concerning the detection of E. coli O157.H7 in artificially contaminated minced beef. The influencing variables are the factors enrichment time, inoculation density, enrichment broth, subculturing medium, and state of samples (fresh vs. deep frozen). The statistical reanalysis displayed strongly differing results emphasizing the importance of interactions in logistic regression models. In particular, the odds ratio for E. coli detection dependant from the enrichment time (24 h vs. 6 h) (OR = 0.41) was strongly overestimated without simultaneous attention of the E. coli inoculation density (OR approximately equal to 0.2 to 0.02). In this context the possible interpretation of the interaction is discussed.

Animals↗

PubMed2000

Optimal designs for the individual and joint exposure general logistic regression models.

Interest in administering compounds in combination lies both in enhancing efficacious effects and in limiting adverse effects. Although much statistical work has focused on developing mathematical functions to model the joint dose-response curves, relatively little work exists in regard to designing experiments for assessing joint action. A variety of parametric dose-response models based on either the normal or logistic probability distribution have been proposed in the literature. These models are typically nonlinear in the parameters, and as such, a nonlinear weighted least squares approach can be employed for the purpose of designing experiments. The approach is applicable across a wide variety of settings commonly associated with joint action data, including continuous and discrete responses, alternative error structures, and nonzero background response. Further, designs can be expressed in terms of proportionate responses associated with the individual compounds rather than dose levels, thereby providing for results that are applicable across compounds. As a precursor to this effort, optimal and minimal experimental designs for the case in which a single compound is administered have also been developed. Although the proposed methodology for deriving experimental designs can be applied to any nonlinear regression model, primary focus is given to the additive and nonadditive independent joint action (IJA) models for individual and combined exposures proposed by Barton, Braunberg, and Friedman (1).

Dose-Response Relationship, Drug↗

PubMed2002

A logistic mixture model for characterizing genetic determinants causing differentiation in growth trajectories.

The logistic or S-shaped curve of growth is one of the few universal laws in biology. It is certain that there exist specific genes affecting growth curves, but, due to a lack of statistical models, it is unclear how these genes cause phenotypic differentiation in growth and developmental trajectories. In this paper we present a statistical model for detecting major genes responsible for growth trajectories. This model is incorporated with pervasive logistic growth curves under the maximum likelihood framework and, thus, is expected to improve over previous models in both parameter estimation and inference. The power of this model is demonstrated by an example using forest tree data, in which evidence of major genes affecting stem growth processes is successfully detected. The implications for this model and its extensions are discussed.

Crosses, Genetic↗

PubMed2004

Sonographic assessment of non-malignant ovarian cysts: does sonohistology exist?

BACKGROUND: Transvaginal ultrasound (TVU) is feasible and accurate in the differentiation between non-malignant and malignant ovarian abnormalities. However, despite the clinical relevance, the accuracy of TVU in the differentiation between the many different non-malignant cysts is unknown. METHODS: Between 1992 and 2002, all women who had surgery at our centre because of a non-malignant ovarian cyst were included prospectively in this study. The sonographic characteristics as well as the expected histological diagnosis (the 'sonohistological diagnosis') were evaluated pre-operatively. This diagnosis was compared with the histopathological diagnosis, and diagnostic parameters [with 95% confidence interval (CI)] of the sonohistological diagnosis were calculated. Logistic models, with the sonographic characteristics as variables, were constructed for each histopathological diagnosis. RESULTS: A total of 406 women were included consecutively. The overall diagnostic accuracy of the sonohistological diagnosis was 60% (95% CI 0.56-0.65). Only in cases of simple ovarian cysts did the diagnostic accuracy of the respective logistic model exceed that of the sonohistological diagnosis (0.88 versus 0.81, P < 0.01). The diagnostic accuracy of the sonohistological diagnosis for endometriotic and dermoid ovarian cysts was significantly better compared with the respective logistic model (0.84 versus 0.71, P < 0.01 and 0.87 versus 0.82, P = 0.03, respectively). CONCLUSION: In approximately half of the non-malignant ovarian cysts, TVU is capable of distinguishing between the different histopathological diagnoses of non-malignant ovarian masses. Only in the diagnosis of simple ovarian cysts might use of the logistic models be helpful.

Adolescent↗

PubMed2000

Prognostic modelling with logistic regression analysis: a comparison of selection and estimation methods in small data sets.

Logistic regression analysis may well be used to develop a prognostic model for a dichotomous outcome. Especially when limited data are available, it is difficult to determine an appropriate selection of covariables for inclusion in such models. Also, predictions may be improved by applying some sort of shrinkage in the estimation of regression coefficients. In this study we compare the performance of several selection and shrinkage methods in small data sets of patients with acute myocardial infarction, where we aim to predict 30-day mortality. Selection methods included backward stepwise selection with significance levels alpha of 0.01, 0.05, 0. 157 (the AIC criterion) or 0.50, and the use of qualitative external information on the sign of regression coefficients in the model. Estimation methods included standard maximum likelihood, the use of a linear shrinkage factor, penalized maximum likelihood, the Lasso, or quantitative external information on univariable regression coefficients. We found that stepwise selection with a low alpha (for example, 0.05) led to a relatively poor model performance, when evaluated on independent data. Substantially better performance was obtained with full models with a limited number of important predictors, where regression coefficients were reduced with any of the shrinkage methods. Incorporation of external information for selection and estimation improved the stability and quality of the prognostic models. We therefore recommend shrinkage methods in full models including prespecified predictors and incorporation of external information, when prognostic models are constructed in small data sets.

Age Factors↗

PubMed2005

An evaluation of logistic regression models for predicting amphipod toxicity from sediment chemistry.

An empirical screening level approach was developed to assess the probability of toxicity to benthic organisms associated with contaminated sediment exposure. The study was based on simple logistic regression models (LRMs) of matching sediment chemistry and toxicity data retrieved from a large database of field-collected sediment samples contaminated with multiple chemicals. Three decisions were made to simplify the application of LRMs to sediment samples contaminated with multiple chemicals. First, percent mortality information associated with each sediment sample was condensed into a dichotomous response (i.e., toxic or nontoxic). Second, each LRM assumed that toxicity was attributable to a single contaminant. Third, individual contaminants present at low concentrations were excluded from toxic sediment samples. Based on an analysis of the National Sediment Inventory database, the LRM approach classified 55% of nontoxic sediments as toxic (i.e., false-positives). Because this approach has been used to assess the probability of benthic toxicity as reported by the U.S. Environmental Protection Agency (U.S. EPA), the resultant estimates of potential toxicity convey a misleading impression of the increased hazard that sediments pose to the health of aquatic organisms at many sites in the United States. This could result in important resources needlessly being diverted from truly contaminated sites to evaluate and possibly remediate sediments at uncontaminated sites.

Amphipoda↗

PubMed2003

A validated logistic regression model to identify coronary heart disease patients within primary care databases in the United kingdom.

We established the optimal search strategy for identifying coronary heart disease (CHD) patients within the Electronic Patient Record (EPR) of 'paperless' family practices in the UK. Multiple logistic regression modelling (MLRM) and Receiver Operating Characteristic (ROC) curves were used to develop the query. The selected search strategy was validated at 2 additional paperless family practices.

Adult↗

PubMed1997

Biochemical model of logistic regression for early prediction of the etiology of acute pancreatitis.

OBJECTIVE: To define a simple model for the early prediction of the biliary or alcoholic etiology in acute pancreatitis, according to the results of several biochemical variables. PATIENTS AND METHODS: Forty-five patients with acute pancreatitis were included in the study (33 of biliary and 12 of alcoholic etiology). Plasma levels of standard biochemical parameters (glucose, urea, albumin, calcium and C-reactive protein), liver function tests (glutamic oxalacetic transaminase, glutamic pyruvic transaminase, alkaline phosphatase, (gamma-glutamyl-transpeptidase, lactic dehydrogenase, bilirubin and bile acids) and pancreatic enzymes (lipase, amylase and p-amylase) were measured daily throughout the first three days of hospitalization. The lipase/amylase ratio was also calculated. Univariate and logistic regression analyses were performed. RESULTS: Age, sex and plasma levels of C-reactive protein, glutamic oxalacetic transaminase, glutamic pyruvic transaminase, alkaline phosphatase, (gamma-glutamyl-transpeptidase, bilirubin and amylase were significantly different in the two groups. The lipase/amylase ratio was not useful. Logistic regression analysis based on four variables: sex, age, C-reactive protein(day) 1 and glutamic pyruvic transaminase(day) 2 allowed the correct classification in 44 of 45 cases (97.7%). CONCLUSIONS: Biliary and alcoholic acute pancreatitis present differing biochemical profiles-Glutamic pyruvic transaminase(day)2 and C-reactive protein(day) 1 were the variables with the highest predictive value. Taking into account these two biochemical parameters plus age and sex, an accurate and early etiologic classification was possible in the vast majority of cases in the present study.

Acute Disease↗

PubMed2003

Analysis of the logistic function model: derivation and applications specific to batch cultured microorganisms.

Mathematical models are useful for describing microbial growth, both in natural ecosystems and under research conditions. To this end, a rate expression that accounted for depletion of nutrients was used to derive the logistic function model for batch cultures. Statistical analysis was used to demonstrate the suitability of this model for growth curve data. Two linear forms of the model and two procedures for calculating growth rate constants were derived to facilitate statistical evaluation of growth curves. The procedures for calculating growth rate constants were found to be useful for calculation of growth rate constants at each time point, or for estimating growth rate constants from early growth curve data. The utility of the logistic function model and its alternative forms is discussed with respect to planning experiments, analyzing growth curves for the effects of factors other than nutrient limitation, and developing more complete descriptions of cell proliferation.

Bacteria↗

PubMed1990

On the consequences of model misspecification in logistic regression.

Logistic regression models are commonly used to study the association between a binary response variable and an exposure variable. Besides the exposure of interest, other covariates are frequently included in the fitted model in order to control for their effects on outcome. Unfortunately, misspecification of the main exposure variable and the other covariates is not uncommon, and this can adversely affect tests of the association between the exposure and response. We allow the term "misspecification" to cover a broad range of modeling errors including measurement errors, discretizing continuous explanatory variables, and completely excluding covariates from the model. This paper reviews some recent results on the consequences of model misspecification on the large sample properties of likelihood score tests of association between exposure and response.

Animals↗

PubMed2005

Haplotype effects on human survival: logistic regression models applied to unphased genotype data.

Haplotype based linkage disequilibrium (LD) mapping exhibits higher power than the single locus approach because it makes use of the LD information contained in the flanking markers. New statistical methods have been proposed to help to infer haplotype effects on human diseases using multi-locus genotype data collected from unrelated individuals. In this paper, we introduce a statistical procedure for measuring haplotype effects on human survival using the popular logistic regression model with haplotype based parameterizations. By modeling haplotype frequency as a function of age, our model infers haplotype effects by estimating and testing the slope parameters under different genetic mechanisms (multiplicative, dominant, or recessive). In addition, by estimating the sex-specific slope parameters, our model allows the detection of sex-specific haplotype effects or haplotype-sex interactions. As an example, we apply our model to an empirical dataset on a stress related gene, interleukin-6, to look for haplotypes that affect individual survival and for haplotype-sex interactions. We show that our logistic regression based haplotype model can be a helpful tool for researchers interested in the genetics of human aging and longevity.

Female↗

PubMed2000

Segregation analysis of epilepsy in the Belgian tervueren dog.

In 1986, a survey of the incidence of epileptic seizures among dogs in the American Belgian Tervuren Club was undertaken. By 1989, 557 of the 607 members had returned completed surveys, providing seizure information about 938 dogs. The survey classified the dogs into one of four categories: 1) no seizures observed (738 dogs); 2) one seizure observed (26 dogs); 3) two to five seizures observed (82 dogs); and 4) more than five seizures observed (92 dogs). To evaluate the plausibility of a major gene model, a regressive logistic model was applied to these data. The results suggest that a single locus with a large effect on the incidence of seizures may be segregating in this population.

Alleles↗

PubMed2005

A semiparametric two-component "compound" mixture model and its application to estimating malaria attributable fractions.

Malaria remains a major epidemiologic problem in many developing countries. Malaria is defined as the presence of parasites and symptoms (usually fever) due to the parasites. In endemic areas, an individual may have symptoms attributable either to malaria or to other causes. From a clinical viewpoint, it is important to correctly diagnose an individual who has developed symptoms so that the appropriate treatments can be given. From an epidemiologic and economic viewpoint, it is important to determine the proportion of malaria-affected cases in individuals who have symptoms so that policies on intervention program can be developed. Once symptoms have developed in an individual, the diagnosis of malaria can be based on the analysis of the parasite levels in blood samples. However, even a blood test is not conclusive as in endemic areas many healthy individuals can have parasites in their blood slides. Therefore, data from this type of study can be viewed as coming from a mixture distribution, with the components corresponding to malaria and non-malaria cases. A unique feature in this type of data, however, is the fact that a proportion of the non-malaria cases have zero parasite levels. Therefore, one of the component distributions is itself a mixture distribution. In this article, we propose a semiparametric likelihood approach for estimating the proportion of clinical malaria using parasite-level data from a group of individuals with symptoms. Our approach assumes the density ratio for the parasite levels in clinical malaria and nonclinical malaria cases can be modeled using a logistic model. We use empirical likelihood to combine the zero and nonzero data. The maximum semiparametric likelihood estimate is more efficient than existing nonparametric estimates using only the frequencies of zero and nonzero data. On the other hand, it is more robust than a fully parametric maximum likelihood estimate that assumes a parametric model for the nonzero data. Simulation results show that the performance of the proposed method is satisfactory. The proposed method is used to analyze data from a malaria survey carried out in Tanzania.

Animals↗

PubMed2001

Using the Rasch measurement model to investigate the construct of motor ability in young children.

This paper reports the use of a Rasch measurement model, the Extended Logistic Model of Rasch (Andrich, 1988), to explore the construct of a general motor ability in young children. Data were collected from 332 five and six year old children performing 24 motor skills, including run, hop, balance and ball skills. The data were categorised based on threshold estimates provided by the measurement model. Gender differences in performances on items were hypothesised to contribute to initial item and person misfit for the total sample. The data for boys and for girls were separated and independently analysed resulting in improved item and person fit. Two different, unidimensional scales for boys and for girls were created.

Aptitude↗

PubMedDate not supplied

Reversal of hepatoma cells resistance to anticancer drugs is correlated to cell proliferation kinetics, telomere length and telomerase activity.

BACKGROUND: Clinical and experimental observations indicate that resistance to anticancer drugs may be spontaneously reversible over time. MATERIALS AND METHODS: This work is a mathematical and statistical analysis of the relationship, during a 9-month experiment, between the resistance of repeatedly re-seeded hepatoma cells to methotrexate (MTX) or to cisplatin (cisP) and untreated cell proliferation, telomere length and telomerase activity. RESULTS: All variables showed complex oscillations, as previously published. In this work, cell proliferation was modelized by the logistic model, and the proliferation rates (a-values) together with their variations (va-values) were calculated. CONCLUSION: Significant correlations were discovered between cell resistance to treatments and a-values, va-values, telomere length and telomerase activities. These results open new insights into the handling of chemotherapy in the treatment of cancers.

Animals↗

PubMed1990

Rib fractures in children: a marker of severe trauma.

The early recognition of life-threatening injury is paramount to the prompt initiation of appropriate care. This study assesses the importance of multiple rib fractures as a marker of severe injury in children. We analyzed physiologic, etiologic, and injury data for 2,080 children with blunt or penetrating trauma aged 0-14 years consecutively admitted to a Level I pediatric trauma center. Analysis of variance, Student's t-test, and the Chi-square test of independence were used to test for differences between children with rib fractures and other children. Probability of survival was modeled using stepwise logistic regression. There were 14 deaths among 33 children with rib fractures, a mortality rate of 42%. Child abuse accounted for 63% of the injuries to children less than 3 years old, while pedestrian injuries predominated among older children. Children with rib fractures were significantly more severely injured than children with blunt or penetrating trauma but without rib fractures. When compared to children without rib fractures, children with rib fractures had a higher mortality rate, but no statistically significant difference in morbidity. The mortality rate for the 18 children with both rib fractures and head injury was 71%. A logistic model with variables measuring severity of head injury and number of ribs fractured correctly predicted survival in more than 85% of children with thoracic trauma. Although rib fractures are rare injuries in childhood, they are associated with a high risk of death. The risk of mortality increases with the number of ribs fractured. The combination of rib fractures and head injury was usually fatal.

Adolescent↗

PubMed2007

A weighted logistic regression model for estimation of recurrence of adenomas.

In a colorectal polyp prevention trial, some participants might have their follow-up colonoscopy conducted before the scheduled time (i.e. at the end of the trial). This results in variable follow-up lengths for participants and the data of recurrence status at the end of the trial can be considered as current status data. In this paper, we use a weighted logistic regression model to estimate recurrence rate of adenoma data at the end of the trial. The weights are used to adjust for variable follow-up. We show that logistic regression tends to underestimate recurrence rate. In a simulation study, we show that Kaplan-Meier estimator derived from the right endpoint of the current status data tends to overestimate recurrence rate in contrast to logistic regression and the weighted logistic regression method can produce reasonable estimates of recurrence rate even under a high non-compliance rate compared to conventional logistic regression and Kaplan-Meier estimator. The method described here is illustrated with an example from a colon cancer study.

Adenoma↗