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At least 487 records · Page 27Linked to original sources
PubMed1976

A statistical model of the dynamics of a mosquito vector (Culex tarsalis) population.

A model of the dynamics of a mosquito Culex tarsalis is derived that includes the life states through which the mosquito proceeds. Transition probabilities from one state (egg, larva, pupa and adult) to another are derived and they depend on the duration of stay and mortality in each state. A formula is derived for the expected number of mosquitoes alive at any time during the spring or summer. This formula depends on the number of eggs oviposited and the transition probabilities. Data are used to estimate the parameters and to illustrate the usefulness of this model in examining the effect of changes in mosquito survival on the dynamics of the population.

Animals↗
PubMed1989

Anaerobic threshold estimation by statistical modelling.

Anaerobic threshold (AT) is usually estimated as a change point problem by visual analysis of the cardiorespiratory response to incremental dynamic exercise. In this study, two phase linear (TPL) models of the linear-linear and linear-quadratic type were used for the estimation of AT. The correlation coefficient between the classical and statistical approaches was 0.88, and 0.89 after outlier exclusion. The TPL models provide a simple method for estimating AT that can be easily implemented using a digital computer for the automatic pattern recognition of AT.

Anaerobic Threshold↗
PubMed2002

Predicting the success of primer extension genotyping assays using statistical modeling.

Using an empirical panel of more than 20 000 single base primer extension (SNP-IT) assays we have developed a set of statistical scores for evaluating and rank ordering various parameters of the SNP-IT reaction to facilitate high-throughput assay primer design with improved likelihood of success. Each score predicts either signal magnitude from primer extension or signal noise caused by mispriming of primers and structure of the PCR product. All scores have been shown to correlate with the success/failure rate of the SNP-IT reaction, based on analysis of assay results. A logistic regression analysis was applied to combine all scored parameters into one measure predicting the overall success/failure rate of a given SNP marker. Three training sets for different types of SNP-IT reaction, each containing about 22 000 SNP markers, were used to assign weights to each score and optimize the prediction of the combined measure. c-Statistics of 0.69, 0.77 and 0.72 were achieved for three training sets. This new statistical prediction can be used to improve primer design for the SNP-IT reaction and evaluate the probability of genotyping success for a given SNP based on analysis of the surrounding genomic sequence.

DNA Primers↗
PubMed1991

Statistical modeling of prognostic indices for evaluation of critically ill patients.

OBJECTIVE: To identify the most predictive association of variables from the usual indices of severity of illness by statistical objective analysis. DESIGN: Logistic regression analysis of the different variables of the most important indices. SETTING: A general critical care medicine group practice in a university hospital. PATIENTS: A total of 630 critical care patients age 12 to 87 yrs were evaluated. The most important indices of severity of illness and the corresponding variables were recorded and the patient's course was followed for 3 months after ICU admission. MEASUREMENTS AND MAIN RESULTS: One of our hypotheses was that the inclusion of an excessive number of variables to obtain the most common prognostic indices of mortality in critical care patients results in an underestimation of mortality and a redundancy of prognostic information. We performed a logistic regression analysis using the variables of the currently used indices of critical care prognosis: Acute Physiology Score, Simplified Acute Physiology Score, Acute Physiology Score-II, and Mortality Prediction Model. This mathematical approach resulted in a model of five variables: organ system failure, blood glucose, serum calcium, serum prothrombin activity, and serum osmolality. The score obtained from this model gave accurate prognostic criteria:sensitivity 91.2% and specificity 90%, using a cutoff point of 0.7; sensitivity 86% and, specificity 94%, using a cutoff point of 0.5. CONCLUSIONS: Our results show that suitable statistical management of the discriminant prognostic variables allows reduction of the number of variables of the severity indices currently used, obtaining five more predictive variables.

Adolescent↗
PubMed2006

A computationally efficient approach to the estimation of two- and three-dimensional hidden Markov models.

Statistical modeling methods are becoming indispensable in today's large-scale image analysis. In this paper, we explore a computationally efficient parameter estimation algorithm for two-dimensional (2-D) and three-dimensional (3-D) hidden Markov models (HMMs) and show applications to satellite image segmentation. The proposed parameter estimation algorithm is compared with the first proposed algorithm for 2-D HMMs based on variable state Viterbi. We also propose a 3-D HMM for volume image modeling and apply it to volume image segmentation using a large number of synthetic images with ground truth. Experiments have demonstrated the computational efficiency of the proposed parameter estimation technique for 2-D HMMs and a potential of 3-D HMM as a stochastic modeling tool for volume images.

Algorithms↗
PubMed2001

Evaluating data from behavioral analysis: visual inspection or statistical models?

Traditional behavior analysis relies upon single-subject study designs and visual inspection of graphed data to evaluate the efficacy of experimental manipulations. Attempts to apply statistical inferential procedures to analyze data have been successfully opposed for many decades, despite problems with visual inspection and increasingly cogent arguments to utilize inferential statistics. In a series of experiments, we show that trained behavior analysts often identify level shifts in responding during intervention phases ('treatment effect') in modestly autocorrelated data, but trends are either misconstrued as level treatment effects or go completely unnoticed. Errors in trend detection illustrate the liabilities of using visual inspection as the sole means by which to analyze behavioral data. Meanwhile, because of greatly increased computer power and advanced mathematical techniques, previously undeveloped or underutilized statistical methods have become far more sophisticated and have been brought to bear on a variety of problems associated with repeated measures data. I present several nonparametric procedures and other statistical techniques to evaluate traditional behavioral data to augment, not replace, visual inspection procedures.

Journal Article↗
PubMed2005

Spatial statistical modeling of disease outbreaks with particular reference to the UK foot and mouth disease (FMD) epidemic of 2001.

In this paper we examine issues relating to the analysis of spatially-referenced disease data. Initially, we discuss the use of exploratory statistical tools such as density estimation and nonparametric regression. We then consider the need for descriptive epidemic models in space, time, and space-time models for epidemic dynamics. Implicitly space-time must be considered in any analysis of the spatial structure of epidemics. The use of Bayesian models for disease spread is discussed and applied to the recent foot and mouth outbreak in the UK.

Animals↗
PubMed1994

Aedes albopictus (Diptera: Culicidae): a statistical model of the role of temperature, photoperiod, and geography in the induction of egg diapause.

Aedes albopictus (Skuse) lays eggs refractory to hatching in response to several environmental cues. The goal of this statistical treatment was to quantify the role and interaction of latitude and country of origin (Japan and the United States), photoperiod, rearing/holding temperature, and a newly identified element, elevation of the site of origin, with critical photoperiod (Cpp). We also describe the development of an equation relating the incidence of diapause to daylength, rearing/holding temperature, and latitude and elevation of the site of origin, an equation useful in the development of a simulation model of the population dynamics and distribution of Ae. albopictus in North America. The analysis indicated that elevation from 0 to 300 m is significantly correlated with Cpp. The results also corroborate earlier conclusions that, on the basis of a shallower geographical cline in photoperiodic response in the United States, North American strains of Ae. albopictus have a temperate origin in Asia and indicate that the rapid spread of this mosquito within the United States via the distribution of used tires resulted in founder populations that were only partially adapted in diapause response to local conditions.

Aedes↗
PubMed1990

Statistical modeling of selected aspects of the childbearing process with application to World Fertility Survey countries.

"A mathematical model for estimation of certain aspects of the childbearing process, which requires only data on age-specific fertility rates, is developed. Synthetic maternal childbearing indices, namely, mean ages at first and last birth, length of reproductive life span, inter-birth spacing, and proportion of childless women, in addition to the well-known mean age at childbearing, for the WFS [World Fertility Surveys conducted in developing] countries are obtained using the proposed model. The indices are free from age truncation effects, and, under certain assumptions, provide information about a cohort's completed fertility before the women stop reproducing. The effects of women's residence and education on fertility are also examined." (SUMMARY IN FRE)

Age Factors↗