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PubMed1999

A mathematical model with a modified logistic approach for singly peaked population processes.

When a small number of individuals of a single species are confined in a closed space with a limited amount of indispensable resources, breeding may start initially under suitable conditions, and after peaking, the population should go extinct as the resources are exhausted. Starting with the logistic equation and assuming that the carrying capacity of the environment is a function of the amount of resources, a mathematical model describing such a pattern of population change is obtained. An application of this model to a typical set of population records, that of deer herds by V. B. Scheffer (1951, Sci. Monthly 73, 356-362) and E. C. O'Roke and F. N. Hamerstrom (1948, J. Wildlife Management 12, 78-86), yields estimates of the initial amount of indispensable food and its availability or nutritional efficiency which were previously unspecified.

Animals↗
PubMed1994

Logistic regression analysis of twin data: estimation of parameters of the multifactorial liability-threshold model.

We extend the DeFries-Fulker regression model for the analysis of quantitative twin data to cover binary traits and genetic dominance. In the proposed logistic regression model, the cotwin's trait status, C, is the response variable, while the proband's trait status, P, is a predictor variable coded as k (affected) and 0 (unaffected). Additive genetic effects are modeled by the predictor variable PR, which equals P for monozygotic (MZ) and P/2 for dizygotic (DZ) twins; and dominant genetic effects, by PD, which equals P for MZ and P/4 for DZ twins. By setting an appropriate scale for P (i.e., the value of k), the regression coefficients of P, PR, and PD are estimates of the proportion of variance in liability due to common family environment, additive genetic effects, and dominant genetic effects, respectively, for a multifactorial liability-threshold model. This model was applied to data on lifetime depression from the Virginia Twin Registry and produced results similar to those from structural equation modeling.

Adult↗
PubMed1993

Reduction in the risk of bronchopulmonary dysplasia from 1980-1990: results of a multivariate logistic regression analysis.

A retrospective analysis (1980-1990) of normally formed low birthweight (< 2500 g) infants surviving to at least 28 days following intermittent positive pressure ventilation (IPPV) for longer than 12 h was performed. Bronchopulmonary dysplasia (BPD) was defined as oxygen dependency at 28 days with characteristic radiographic findings. Logistic regression analysis of risk factors, before and after the initiation of IPPV was performed on 412 infants. Decreasing birth weight (BW) and gestational age (GA) were associated with an increased risk of BPD. When controlled for these variables, predictive factors prior to IPPV were gender, age at IPPV, respiratory diagnosis, and year of birth. Following IPPV, duration of peak inspiratory pressure > 25 cm H2O, duration of fraction of inspired oxygen (FiO2) > 0.60 (DO2), maximum peak inspiratory pressure (MPIP), maximum FiO2, patent ductus arteriosus, bacteraemia and either pneumothorax or pulmonary interstitial emphysema were associated with an increased risk of BPD. Adjusting for BW and GA, there was a significant reduction in BPD risk from 1980-1990 (relative odds of 0.88 for each year compared to the previous year). This trend could be largely accounted for by decreases in MPIP and DO2 during the study period. Surfactant treatment was not independently associated with a significant change in the risk of BPD. Based on this analysis, we developed a scoring system for predicting the risk of BPD in the neonatal period which we evaluated in a random sample of infants. This predicted infants at risk of BPD with a sensitivity of 65% and a specificity of 88%.(ABSTRACT TRUNCATED AT 250 WORDS)

Birth Weight↗
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↗
PubMed2006

Biochemical data in ornithine transcarbamylase deficiency (OTCD) carrier risk estimation: logistic discrimination and combination with genetic information.

One-fifth of the gene mutations causing ornithine transcarbamylase deficiency cannot be detected. In such cases carrier risk estimation must refer to biochemical data-such as increased plasma glutamine concentration or increased orotidine excretion after allopurinol load -although these parameters do not yield a definite diagnosis. Here, I derive odds for carrier risk estimation from published data, i.e. from mean and standard deviation of glutamine concentrations in carriers and noncarriers, assuming normal distributions, and from allopurinol test results in individual carriers and noncarriers using logistic regression. I show how such biochemical information may be combined with genetic information, thus demonstrating the usefulness of biochemical data. The necessity to assess individual results in larger proband groups and to consider possible correlations between different parameters is indicated.

Allopurinol↗
PubMedDate not supplied

An empirical method to refine personality disorder classification using stepwise logistic regression modeling to develop diagnostic criteria and thresholds.

This study of DSM-III-R personality disorder (PD) classification provides an empirical approach to determine (1) the discriminative power of each criterion and (2) the optimal number of criteria needed to diagnose the presence of each PD. A semistructured assessment of 110 outpatients was performed for the 11 PDs and their 104 diagnostic criteria. Sensitivity, specificity, and predictive powers were calculated for each criterion item. Logistic regression was performed to determine (1) univariate weightings of the individual criteria as applied to a given diagnosis, and (2) multivariate measures of the criteria that significantly improved the chi-square value in a stepwise fashion. The significant items were then equally weighted to calculate the optimal number needed to diagnose category membership. Of 104 PD criteria, 41 discriminated at a significance level of .05 or less, and each PD could be optimally diagnosed with fewer criteria than currently required. We can empirically reduce the number of criteria combinations comprising individual categories, decrease heterogeneity, and narrow diagnostic boundaries. This increases the likelihood of identifying etiological factors, predictors of clinical course, specific treatments, familial aggregation, and neurobiological correlates for the PD taxa.

Adolescent↗
PubMed1995

Logistic equations in the analysis of S-shaped curves.

A version of the logistic equation that provides useful descriptive parameters for the asymptote, slope and inflection point of the curve is presented and is suggested for use in empirically fitting S-shaped curves to data. A short SAS program that easily calculates the parameter values is shown.

Bias↗
PubMed1991

Polychotomous multivariate models for coronary heart disease simulation. I. Tests of a logistic model.

Stochastic compartmental modeling techniques have been employed to simulate coronary heart disease morbidity and mortality. In the current paper, polychotomous logistic models are used to describe the relationship between risk of disease and multiple risk factors, effect modification and confounding variables. The process of estimating the parameters for two risk factors and three types of outcomes is described for a population followed for five years. A Statistical Analysis System (SAS) procedure was used to estimate risk factor coefficients based on two partial periods and on the entire five year epoch. Most of the estimated coefficients were found to be statistically significant. The model performance was evaluated by comparing the observational data with simulated outcomes using a micropopulation and Monte Carlo techniques. Two different tests of goodness of fit were used. Satisfactory fits were obtained both for the risk coefficients based on two partial periods and those based on the entire epoch. This indicates that the model is suitable for simulation of the effects of intervention strategies. The use of the entire epoch involved estimates of one half as many parameters as did the use of two partial periods. Accordingly, it is concluded that only the entire epoch need be considered for future studies of this population.

Adult↗
PubMed1990

Logistic discriminant analysis of lipids and apolipoproteins in a population of coronary bypass patients and the significance of apolipoproteins C-III and E.

The lipid and apolipoprotein states of 74 men (mean age 49.96 +/- 5.9 years) were studied 24 h before coronary bypass surgery and their results were compared with those of a control group of 78 men (mean age 48.88 +/- 5.41 years). Apolipoproteins C-III (apo C-III) and E (apo E) were determined in particles with (LpB) and without (nonLpB) apo B separated using a concanavalin A reagent. Apo C-III was significantly increased in LpB particles (P less than 0.001), and apo E in LpB (P less than 0.001) and nonLpB (P less than 0.001) particles. The significant variables selected in logistic discriminant stepwise analysis were total cholesterol/HDL-cholesterol, apo E-nonLpB and apo C-III-LpB. This last parameter, which is more discriminant than triglycerides, provides a more specific indication of dyslipoproteinemia in coronary bypass patients; in association with the other two variables, it significantly improved the percentage of correctly classified individuals.

Adult↗
PubMed1986

Background factors of ectopic pregnancy. II. Risk estimation by means of a logistic model.

Based on the frequency distribution in a previous case-control study of ectopic pregnancy in Sweden, the prognostic value of a number of risk factors was analysed. A logistic procedure was applied in a stepwise manner, resulting in a risk-scoring model in which the probability of ectopic pregnancy can be determined on the basis of four background factors.

Abdomen↗
PubMed1994

Application of a log-logistic model to describe the survival of Yersinia enterocolitica at sub-optimal pH and temperature.

A log-logistic model previously used to describe the thermal inactivation of microorganisms has been applied to predict accurately the survival of Yersinia enterocolitica under conditions of sub-optimal temperatures (0-23 degrees C) and growth inhibitory pH values for a number of different acidulants. Predictions from the model were also compared to observed survival times of Y. enterocolitica in mayonnaise and were found to be in excellent agreement. However in yoghurt the model overestimated survival of this organism at both 20 and 4 degrees C but would 'fail safe' if used for predictive purposes. The discrepancy in yoghurt is discussed.

Food Microbiology↗
PubMed1990

Examination by logistic regression modelling of the variables which increase the relative risk of elderly women falling compared to elderly men.

In a community based, prospective study to determine risk factors for falls, 465 women and 296 men 70 years and over were followed for 1 year and 507 falls were documented. A greater proportion of women (32.7%) than men (23.0%) experienced at least one fall in which there was no or minimal external contribution. Using unconditional logistic regression models we investigated the effect of physical and sociological variables on the sex difference in fall rate. Controlling for the variables age, use of psychotropic drugs, inability to rise from a chair without using arms, going outdoors less than daily and living alone decreased the relative risk of women falling compared to men from 2.02 (95% CI, 1.40-2.92) to 1.55 (95% CI 1.04-2.31). Some of the increased risk of falling associated with being a women was able to be explained and is potentially correctable. But even after controlling for the physical and social variables which we had assessed, women compared to men still had a significantly increased relative risk of falling.

Accidental Falls↗
PubMed1990

Identification of high risk groups for breast cancer by means of logistic models.

In order to identify high risk groups for breast cancer, unconditional multiple logistic regression models based on 5 widely recognized and easily identifiable risk factors (age at menarche, at menopause and at first birth, family history of breast cancer and body mass index) were applied to a large dataset including 2085 cases and 1936 controls aged 50 or over derived from two unmatched hospital-based case-control studies conducted in Italy. Although various models provided an excellent fitting, both on the whole dataset and using a training-testing approach to a priori identified separate subset, the observed extent of variation in breast cancer risk between highest and lowest decile of the distribution was limited to a factor 2. This indicates that the 5 variables considered did not allow identification of subgroups with substantially elevated risk of breast cancer to have practical implications for screening/prophylactic treatment purposes.

Adolescent↗
PubMed1992

The logistic modeling of sensitivity, specificity, and predictive value of a diagnostic test.

A method is described for modeling the sensitivity, specificity, and positive and negative predictive values of a diagnostic test. To model sensitivity and specificity, the dependent variable (Y) is defined to be the dichotomous results of the screening test, and the presence or absence of disease, as defined by the "gold standard", is included as a binary explanatory variable (X1), along with variables used to define the subgroups of interest. The sensitivity of the screening test may then be estimated using logistic regression procedures. Modeled estimates of the specificity and predictive values of the screening test may be similarly derived. Using data from a population-based study of peripheral arterial disease, the authors demonstrated empirically that this method may be useful for obtaining smoothed estimates of sensitivity, specificity, and predictive values. As an extension of this method, an approach to the modeling of the relative sensitivity of two screening tests is described, using data from a study of screening procedures for colorectal disease as an example.

Arterial Occlusive Diseases↗
PubMed2004

Impact of infrastructure and local environment on road unsafety. Logistic modeling with spatial autocorrelation.

This article aims at modeling the impact of road characteristics and local spatial environment on road (un)safety. The study applies to Belgium where some 1,500 people are killed annually on the roads. This statistic corresponds to one of the highest risks in Europe. Road unsafety is expressed here as whether an hectometer of road belongs to a black zone; a black zone is defined as a segment of road where roads accidents are concentrated. Logistic modeling including spatial autocorrelation is used and compared to non-spatial regression. It is shown that a spatial model is needed to avoid biased estimated parameters. Results show that local environment and road infrastructure play a substantial role in the co-occurrence of road accidents. Hence, education and enforcement cannot be the only measures taken to reach a sustainable road safety. To attain their objectives of accident reduction, public authorities should also take their responsibilities in the matter of securing road infrastructure.

Accidents, Traffic↗
PubMed2006

Switchgrass (Panicum vigratum, L.) delivery to a biorefinery using integrated biomass supply analysis and logistics (IBSAL) model.

This study develops cost, energy input and carbon emissions for a number of switchgrass supply options. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model developed at Oak Ridge National Laboratory is used to evaluate the delivery systems. Three biomass collection systems: baling, loafing and ensiling are evaluated. The number and operational performance of equipment are specified to complete collection operations within 120 days of harvest after August 1. Bales are stacked and tarped on the farm side. The transport of biomass from the farm side to a biorefinery takes place over a full year cycle, i.e. 365 days. Supply quantities range from 454 to 4540 dry tonnes/day (500-5000 dry tons/day). Delivered costs to a biorefinery with capacity of 1814 dry tonnes/day (2000 dry tons/day) are: 44-47 dollars/dry tonne for delivered bales (round and square); 37 dollars/dry tonne for delivered loafs (size 2.4 m x 3.6 m x 6 m); 40 dollars/dry tonne for chopped biomass; and 48 dollars/dry tonne for ensiled chops. These costs do not include any payment to the farmers or switchgrass farming cost. Based on the data from literature, the switchgrass farming cost can range from 30 to 36 dollars/dry tonne. These costs would be additional to the switchgrass collection and transportation cost. Switchgrass collection is generally less expensive than collection of straw or corn stover because of the assumed high yield of 11 dry tonnes/ha and a denser biomass. Energy consumption for delivery systems at this capacity ranges from 4.8% to 6.3% of the energy content of switchgrass. Additional 1% of the energy content of switchgrass is consumed in its farming. At 1814 dry tonnes/day (2000 dry tons/day) capacity, greenhouse gas emissions ranges from 75 to 100 kg of CO2/dry tonne of switchgrass delivered.

Air Pollution↗
PubMed2005

Free knot splines for logistic models and threshold selection.

The logistic regression model has been in use in statistical analysis for many years. The paper introduces a spline model to remove the linear restriction on logit function. By considering knot locations as free variables, spline approximation of data is improved. The number of knots and the degree of the spline functions can still be determined by using a model selection procedure. Moreover, a knot, seen as a free parameter for a piecewise linear spline, represents a break point in the logit function which may be interpreted as a threshold value. This method is applied to a clinical trial for an in vitro fertilization program.

Clinical Trials as Topic↗
PubMed2006

Predictive indicators of deep venous thrombosis and pulmonary arterial thromboembolism in 54 subjects after total knee arthroplasty using multislice computed tomography in logistic regression models.

PURPOSE: To determine predictors of deep venous thrombosis (DVT) in the lower extremities and pulmonary arterial thromboembolism (PE) after total knee arthroplasty (TKA), we evaluated the incidence of these events using multislice computed tomography (CT). METHODS: 54 subjects (10 males, 53-81 years old, the first consecutive 25 receiving anticoagulant therapy) underwent enhanced multislice CT (MSCT) before and one week after TKA. RESULTS: DVT, PE, and both were detected in twelve, twelve, and three subjects, respectively, one week after TKA. Hemoglobin and alveolar-arterial oxygen gradient (AaDO2) on the day after TKA, and total amount of operative bleeding (TAOB) were significantly higher in subjects with DVT or PE (P<0.05). In a logistic model for predicting DVT or PE, hemoglobin and AaDO2 levels on the day after TKA and TAOB were associated with an increased incidence of DVT or PE (relative risks 3.51, 1.19 and 1.01 (P<0.05), respectively). From box and whisker plots, we speculated the significant border to predict DVT or PE as 10.5 g/dl for hemoglobin, 34 Torr for AaDO2, and 1280 ml for TAOB. These factors also predicted DVT or PE (relative risks 5.08 (hemoglobin more than 10.5), 6.25 (AaDO2 more than 34 Torr), and 4.95 (TAOB more than 1280 ml) (P<0.05)). CONCLUSIONS: The incidence of DVT or PE one week after TKA was 39% by MSCT. High levels of TAOB, hemoglobin and AaDO2 on the day after TKA may be predictive indicators of DVT or PE one week after TKA.

Aged↗