Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Models, Statistical”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10Linked to original sources
PubMed1992

[Data analysis by statistical models].

The basic idea for the realization of effective statistical data analysis is illustrated with an example. The use of statistical models is explained and the feasibility of objective comparison of the models by an information criterion AIC is demonstrated. Further, the possibility of practical use of Bayesian models for complex data analysis is explained. Finally, the necessity of cooperation between the experts of respective fields and statisticians for further development of statistical data analysis is mentioned.

Adult↗
PubMed1984

Sense and nonsense in genetic epidemiology: a critique of the statistical model of Williams and Iyer.

The statistical model for the analysis of twin-family data of Williams and Iyer is examined. The model uses a large number of redundant parameters. It does not lead to quantitative predictions for new relationships. It allows for epistasis but not dominance. It makes assumptions about assortative mating which are inconsistent with any biologically plausible mechanism. It assumes that the environmental correlation between parent and offspring is due to the direct effect of the parental genotypes, not phenotypes, on offspring environment. Other models which avoid these problems are more appropriate for the analysis of extended twin-family data.

Analysis of Variance↗
PubMed1993

Static secondary ion mass spectrometric investigation of the surface chemistry of organic plasma-deposited films created from oxygen-containing precursors. 3. Multivariate statistical modeling.

Partial least squares (PLS) multivariate statistical models were developed to predict the surface composition and chemistry of a set of model homopolymers based on their static SIMS fragmentation patterns. In the calibration or model-building step, the positive and negative ion static SIMS spectra of different classes of model homopolymers were related to specific chemical attributes of the polymers. The models were then used to examine the surface chemistry of oxygen-containing plasma-deposited films prepared from a variety of precursors. PLS models were developed to predict the surface oxygen concentration and H/C ratios. The results obtained from the PLS models were compared with experimental results.

Analysis of Variance↗
PubMed2007

Statistical modelling of Poisson/log normal data.

In statistical data fitting, self consistency is checked by examining the closeness of the quantity chi(2)/NDF to 1, where chi(2) is the sum of squares of data minus fit divided by standard deviation, and NDF is the number of data minus the number of fit parameters. In order to calculate chi(2) one needs an expression for the standard deviation. In this note several alternative expressions for the standard deviation of data distributed according to a Poisson/log-normal distribution are proposed and evaluated by Monte Carlo simulation. Two preferred alternatives are identified. The use of replicate data to obtain uncertainty is problematic for a small number of replicates. A method to correct this problem is proposed. The log-normal approximation is good for sufficiently positive data. A modification of the log-normal approximation is proposed, which allows it to be used to test the hypothesis that the true value is zero.

Computer Simulation↗
PubMed2006

A statistical model predicting high hepatocyte proliferation index and the risk of developing hepatocellular carcinoma in patients with hepatitis C virus-related cirrhosis.

BACKGROUND: Incidence of hepatocellular carcinoma in hepatitis C virus-related cirrhosis is 4% per year. Although cost-effective, current screening could be improved. AIM: To develop a statistical model including non-invasive parameters able to identify patients at high risk of developing hepatocellular carcinoma. METHODS: One hundred and fifty-eight patients (73F:85M) with compensated chronic hepatitis C virus liver disease underwent evaluation, including argyrophilic nucleolar organizer regions proliferation index, and were followed up for 56.18 +/- 1.44 months. RESULTS: Fifty-six patients had chronic hepatitis without cirrhosis and low argyrophilic nucleolar organizer regions proliferation index (< or =25%), 65 had hepatitis C virus-related cirrhosis and low argyrophilic nucleolar organizer regions proliferation index and 37 had hepatitis C virus-related cirrhosis and high argyrophilic nucleolar organizer regions proliferation index (>25%). Groups were similar for gender and viral genotype distribution. None of the patients with chronic hepatitis without cirrhosis developed hepatocellular carcinoma, compared with 6.1% of low argyrophilic nucleolar organizer regions proliferation index and 30.6% of high argyrophilic nucleolar organizer regions proliferation index (P = 0.002). By multivariable logistic regression analysis, the following parameters were independently associated with hepatocellular carcinoma development and used for the development of the statistical model: platelets (OR 0.98), gamma-globulins (OR 0.111), alanine aminotransferase/aspartate aminotransferase ratio (OR 0.07), serum ferritin (OR 1.0) and ultrasonographic pattern (coarse OR 2.9, coarse nodular OR 10.12). The statistical model properly allocated 95.9% of patients with low argyrophilic nucleolar organizer regions proliferation index and 72.2% of patients with high argyrophilic nucleolar organizer regions proliferation index. CONCLUSIONS: The model, to be validated in large prospective studies, may help tailoring screening according to the risk of hepatocellular carcinoma development.

Adult↗
PubMed1995

1988: use of a Bayesian statistical model for risk assessment in coronary artery surgery. Updated in 1995.

A computerized statistical model based on the theorem of Bayes was developed to predict mortality after coronary artery bypass grafting. From January, 1984, to April, 1987, at our hospital, 700 patients underwent isolated coronary artery bypass grafting. The presence or absence of 20 risk factors was determined for each patient. The first 300 patients formed the initial database of the Bayesian predictive model, and the remaining 400 patients were prospectively evaluated in four groups of 100 each. Each group was prospectively evaluated and then incorporated into the database to update the model. There was good agreement between predicted and observed results. Bayesian theory is particularly suited to this task because it (1) accommodates multiple risk factors, (2) is tailored to one's specific practice, (3) determines individual, rather than group, prognosis, and (4) can be updated with time to compensate for a changing patient population. These flexible attributes are especially valuable in light of recent changes in the coronary artery bypass graft patient profile.

Bayes Theorem↗
PubMed2006

Comparison of statistical models for analyzing genotype, inferred haplotype, and molecular haplotype data.

This report compares statistical models based on molecular and inferred haplotypes of the human paraoxonase-1 gene (PON1). In a study of 402 women comprising three race/ethnicities, 137 women had ambiguous inferred haplotypes. The inferred haplotypes (the one with highest posterior probability) for 20 of these women differed from molecular haplotypes, while based on the posterior distribution from the imputation method, 30 discrepancies were expected. We examined the proportion of the variance in PON1 enzymatic activity (phenotype) explained by genotype, and by inferred and molecular haplotype information. For Caucasians, there was an improvement in adjusted R(2) from 16% for the genotype count model, to 29% for imputed haplotypes, and a further improvement to 33% for molecular haplotypes. For Hispanics and African-Americans, there was no indication that haplotypes helped in explaining PON1 activity, and the imputed model gave essentially the same R(2) as the molecular model. For African-Americans, none of the models had adjusted R(2) that exceeded 4%, while for Hispanics they were all about 21-22%. We propose a new parsimonious model which uses all the genotype information and selected haplotype information. For PON1, this model achieves essentially the same adjusted R(2) as the all-haplotype model, with a potential cost savings and without giving the extreme predictions for uncommon haplotype combinations that the all-haplotype models provides.

Aryldialkylphosphatase↗
PubMed1997

Has regional variation in mortality rates declined since 1931, and in all age groups, in Britain? A re-analysis using formal statistical modelling.

STUDY OBJECTIVE: To examine changes in regional variance in all cause mortality rates in Great Britain from 1931-91 using formal statistical modelling procedures, and to follow up the suggestion by Illsley and Le Grand that there has been a reduction over time in the regional variance in younger but not older age groups. DESIGN, SETTING, AND PARTICIPANTS: Data were the age and sex specific death rates around each census from 1931-91 for the British regions, reconstructed to make them comparable with the 1981 regional definitions. Regional variance was modelled using bootstrap simulation tests and by age-period and age-cohort models. MEASUREMENTS AND MAIN RESULTS: While there was some evidence of a decline and levelling off of the regional variance over time in older age groups (over 35), the decline in younger age groups was more marked. This broadly confirms previous findings. Parametrising the period effect into linear and quadratic components, with allowance for an increase in regional variance in the war years, gave broadly comparable fit to the data as a model with period as a factor. Models for the changes in regional variance which were based on period effects seemed to provide a better description of the observed variances than those based on birth cohort effects. In the younger (but not older) groups there was evidence of a rise in the regional variance between 1981 and 1991. CONCLUSIONS: The decline in regional variance is larger in younger than in older age groups when allowance is made for the increase in regional variance over the war years. Statistical modelling can provide insights into the data which are not always detected by descriptive analyses. Moreover, they provide a capacity for generalisation beyond the particular data; relationships found can form the basis for studies of replicability, for example, in other countries.

Adolescent↗
PubMed1980

Statistical modeling of epidemiologic data.

The application of statistical modeling to epidemiology may help suggest a form for the mechanism of exposure action. But distinguishing between the entertained biological models is often difficult due to both inadequacies in epidemiologic studies and inaccuracies in the verbal specifications of the hypothesized interaction mechanisms. For example, the independent and interactive effects of asbestos and smoking on the production of lung cancer have not yet been fully established. In the present communication an analysis of illustrative data from a hypothetical case-compeer study was attempted with the estimation of rate ratios and the use of a log-linear model fitting technique. These analyses allow a parametric representation of the testable models. For adequate material they might provide tentative insight as to whether the data would conform more closely to an additive model than to a multiplicative one or to some other advocated pattern of action.

Asbestosis↗
PubMed2002

A statistical model of the aberration structure of normal, well-corrected eyes.

A statistical model of the wavefront aberration function of the normal, well-corrected eye was constructed based on normative data from 200 eyes which show that, apart from spherical aberration, the higher-order aberrations of the human eye tend to be randomly distributed about a mean value of zero. The vector of Zernike aberration coefficients describing the aberration function for any individual eye was modelled as a multivariate, Gaussian, random variable with known mean, variance and covariance. The model was verified by analysing the statistical properties of 1000 virtual eyes generated by the model. Potential applications of the model include computer simulation of individual variation in aberration structure, retinal image quality, visual performance, benefit of novel designs of ophthalmic lenses, or outcome of refractive surgery.

Adult↗
PubMed2005

Individual survival time prediction using statistical models.

Doctors' survival predictions for terminally ill patients have been shown to be inaccurate and there has been an argument for less guesswork and more use of carefully constructed statistical indices. As statisticians, the authors are less confident in the predictive value of statistical models and indices for individual survival times. This paper discusses and illustrates a variety of measures which can be used to summarise predictive information available from a statistical model. The authors argue that models and statistical indices can be useful at the group or population level, but that human survival is so uncertain that even the best statistical analysis cannot provide single-number predictions of real use for individual patients.

Carcinoma, Non-Small-Cell Lung↗
PubMed1995

[A statistical model for evaluation of air microbes in pharmaceutical production areas. Group for the study of microbiology of the AFI].

In this study it has been proposed a statistic model to evaluate results concerning microbial count of the air obtained in areas of pharmaceutical production. Nowadays both official methods and agreement about limits of microbial count to use in production areas in which non sterile forms has been processed, are absent. The proposed statistic model foresees a processing data that admits a building of "Flow Charts". Two flow chart has been built: the "Mean Flow Chart" and the "Range Flow Chart". The "Mean Flow Chart" shows the data distribution around the mean value, the "Range Flow Chart" points out the data variation. In this way it has been established the process natural tolerance and the relative limits assumed by the variable in exam. If values of microbial count result of limit, the causes have to be investigated and it's necessary to take adequate countermeasures.

Air Microbiology↗
PubMed1996

Statistical model fitting Escherichia coli survival data during starvation in artificial sea water.

The survival of Escherichia coli in artificial sea water was studied using linear and nonlinear regression analysis in order to fit the simplest model. The surviving population was evaluated in a rich medium, and two mathematical models, monophase and diphase linear, were considered. The diphase model gave the best fit, although both models can be adjusted to the results obtained. The criteria applied to decide which model was more statistically significant, were residuals, the residual sum of squares and the coefficient of determination. These models are discussed in the light of present day knowledge on survival.

Colony Count, Microbial↗
PubMed2004

Statistical models to optimize production of probiotic characteristics.

The use of probiotic microorganisms has been widely promoted in the last 20 years. Probiotics have applied to the gastrointestinal tract as capsules or as fermented milks. The characteristics of the strains proposed as probiotics have been published or patented after elaboration of the product. The first step in designing a probiotic product is to isolate and characterize strains with beneficial properties. Our group has reported the isolation and characterization of 134 strains of lactobacilli from the vagina of women from our city. Surface properties and the production of antagonistic substances has also been published. From these studies, certain strains were selected because they shared probiotic characteristics. The second step in the design of a pharmaceutical product is to determine the optimal conditions for obtaining the highest amount of viable microorganisms, as well as the best conditions to produce antagonistic substances. To perform these types of experiments, laboratory assays can be carried out to determine the optimum conditions in which the microorganisms can be cultured. Growth parameters and optimal growth conditions can be studied by the classical methodology or by the application of alternative methodologies. Alternative methods have been widely used in the food industry, including experimental designs to test multiple conditions at the same time, complemented by the use of statistical models to evaluate and compare all the conditions tested. The object of this chapter is to describe the experimental designs used to study the technological characteristics of vaginal probiotic lactobacilli as well as the application of statistical models for evaluation of the different conditions tested for the production of biomass and antagonistic substances in these bacteria. With this objective in mind, in the present chapter, the following areas are explored: 1. Growth experiments performed to study the effect of temperature, pH, agitation, and culture media on the growth and production of antagonistic substances by vaginal lactobacilli. 2. Fractional and complete factorial experimental designs used to perform the growth experiments. 3. Statistical models applied to evaluate the growth parameters and their modifications under the conditions assayed.

Bacteriological Techniques↗
PubMed2005

Statistical model of pesticide penetration through woven work clothing fabrics.

Statistical models estimating the level of protection and thermal comfort performance of woven fabrics were developed using simple fabric and liquid parameters. Eighteen woven fabrics were evaluated against three pesticide mixtures of atrazine and pendimethalin at different concentrations. Using three mixtures that represent a range of both surface tension and viscosity, percentages of pesticide penetration are measured, along with fabric thickness, fabric cover factor, yarn twist factor, yarn packing factor, solid volume fraction, wicking height, and air permeability. Statistical analyses are performed to examine the relationship between liquid/fabric parameters and pesticide penetration. Statistical analyses show that fabric cover factor, yarn twist factor, viscosity of pesticide mixture, critical surface tension of solid, and wicking height are significant parameters affecting pesticide penetration. For this purpose, cover factor and twist factor are better parameters in describing the geometry of woven fabrics than solid volume fraction. Modeling of comfort performance of woven fabric based on simple textile parameters shows that the combination of fabric thickness, cover factor, yarn twist factor and yarn packing factor can be used to estimate air permeability of woven fabric. These findings could be used for developing selection charts or tools as guidelines for the selection of personal protective equipment for use in hot, humid environments.

Materials Testing↗
PubMed2004

Experimental validation of a statistical model for evaluating the past or future magnetic field exposures of a population living near power lines.

This study was designed to provide an experimental validation for a statistical model predicting past or future exposures to magnetic fields (MF) from power lines. The model estimates exposure, combining the distribution of ambient MF in the absence of power lines with the distribution of past or future MF produced by power lines. In the study, validation is carried out by comparing exposures predicted by the model with the actual measurements obtained from a large-scale epidemiological study. The comparison was made for a group of 220 women living near a 735 kV power line. Knowing that the individual arithmetic means of MF exposures follow a log-normal distribution, the Pearson correlation between the log-transformed measured means and the calculated ones was determined and found to be 0.77. Predicted values of MF exposures were slightly lower than measured values. The calculated geometric mean of the group was 0.33 microT, compared to 0.38 microT for the measured geometric mean. The present study shows good agreement between the measured MF exposure of an individual inside a house near a 735 kV line and the MF exposure calculated using a statistical model.

Adult↗
PubMed1993

[An application of a linear statistical model in clinical anesthesia practice].

One of the important topics in clinical practice of anesthesia, is "prediction". We have to predict what will happen next after obtaining some imperfect data about the patient. The standard and most popularized method is the one utilizing a linear statistical model. This linear model in prediction is based, in part, on the information theory, which says that the volume of information is the linear combination of its components. One of the characteristic models is linear regression analysis. In this paper, basic structure of linear statistical model and its application are discussed. In particular, problems and pitfalls in its application are demonstrated, focusing on variable selection, multi-colinearity and model checking, which will, I believe, lead us to have an access to this clinically important subject "prediction".

Anesthesia↗