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At least 91 records · Page 5Linked to original sources
PubMed1991

Restenosis after coronary angioplasty: a multivariate statistical model to relate lesion and procedure variables to restenosis. The M-HEART Investigators.

The Multi-Hospital Eastern Atlantic Restenosis Trial group obtained follow-up angiography in 510 patients with 598 successfully dilated coronary lesions who were enrolled in a controlled trial of the effects of a single dose of 1 g of methylprednisolone on restenosis after coronary angioplasty. The overall restenosis rate was 39.6%. The strongest univariate relations to the restenosis rate were found for lesion location (saphenous vein graft, 68%; left anterior descending artery, 45%; left circumflex artery and right coronary artery, 32%; p = 0.002); lesion length (less than or equal to 4.6 mm, 33%; greater than 4.6 mm, 45%; p = 0.001); percent stenosis before angioplasty (less than or equal to 73%, 25%; greater than 73%, 43%; p = 0.005), percent stenosis after angioplasty (less than or equal to 21%, 33%; greater than 21%, 46%; p = 0.017) and arterial diameter (less than 2.9 mm, 44%; greater than or equal to 2.9 mm, 34%; p = 0.036). Two multivariate models to predict restenosis probability were developed with use of stepwise logistic regression. The preprocedural model, which included only variables whose values were known before angioplasty, entered lesion length, vein graft location, left anterior descending artery location, percent stenosis before angioplasty, eccentric lesion and arterial diameter. The postprocedural model, which also included variables whose values were known after angioplasty was performed, was similar to the preangioplasty model except that it also entered postangioplasty percent stenosis and "optimal" balloon sizing but did not enter eccentric lesion. These data indicate that the probability of restenosis after angioplasty is determined predominantly by the characteristics of the lesion being dilated. They are consistent with the known intimal proliferative mechanism of restenosis, offer a means of identifying lesions at unusually high or low risk of restenosis, and of predicting the likelihood that a particular lesion will restenose after angioplasty and provide a rationale for stratification by restenosis probability in the design of future studies of restenosis.

Angioplasty, Balloon, Coronary↗
PubMed2004

Automobile seat comfort prediction: statistical model vs. artificial neural network.

The current automobile seat comfort development process, which is executed in a trial and error fashion, is expensive and outdated. The prevailing thought is that process improvements are contingent upon the implementation of empirical/prediction models. In this context, seat-interface pressure measures, anthropometric characteristics, demographic information, and perceptions of seat appearance were related to an overall comfort index (which was a single score derived from a previously published 10-item survey with demonstrated levels of reliability and validity) using two distinct modeling approaches-stepwise, linear regression and artificial neural network. The purpose of this paper was to compare and contrast the resulting models. While both models could be used to adequately predict subjective perceptions of comfort, the neural network was deemed superior because it produced higher r2 values (0.832 vs. 0.713) and lower average error values (1.192 vs. 1.779).

Anthropometry↗
PubMed2003

The Montréal Rehabilitation Performance Profile: a statistical model for assessing stair descent in children with cognitive impairments.

OBJECTIVES: To characterize the responsiveness of the Montréal Rehabilitation Performance Profile (MRPP); to measure the differential effectiveness of a task-specific (TS) and a task-nonspecific (TNS) motor learning format to promote alternating stair descent in children with cognitive impairments; and to evaluate the relevance of the MRPP to evidence-based practice. DESIGN: Randomized comparison of 2 age-matched groups; psychometric testing of measurement tool. SETTING: School for children with developmental and cognitive impairments. PARTICIPANTS: Ambulatory sample of convenience: 18 children, age 5 to 9 years, with moderate to severe cognitive impairment. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The MRPP variables measured at baseline; end of 10-week intervention; and 5 and 10 weeks postintervention. Analysis of variance for repeated measures and part-whole correlation. RESULTS: Global stair descent performance improved for both TS and TNS groups over time (P=.001). However, a specific acquisition and retention of the alternating pattern of descent was associated with the TS format. CONCLUSION: The MRPP was responsive to small differences in stair descent performance that are specific to the format of the motor learning intervention. The MRPP allows clinicians to determine the timing of the intervention needed to maintain or improve stair descent ability.

Analysis of Variance↗
PubMed2006

Dynamical and statistical models of vertebrate population dynamics.

Population dynamics methodology now powerfully combines discrete time models (with constant parameters, density dependence, random environment, and/or demographic stochasticity) and capture-recapture models for estimating demographic parameters. Vertebrate population dynamics has strongly benefited from this progress: survival estimates have been revised upwards, trade-offs between life history traits have been demonstrated, analyses of population viability and management are more and more realistic. Promising developments concern random effects, multistate and integrated models. Some biological questions (density dependence, links between individual and population levels, and diversification of life histories) can now be efficiently attacked.

Animals↗
PubMed2003

The breakdown of semantic knowledge: insights from a statistical model of meaning representation.

Investigations of patients with semantic category-specific deficits have revealed a wide range of performance and variability in categories that are impaired or spared; this variability presents a challenge to accounts of category specificity. Accounts based only on impairment to semantic features of a particular type (e.g., visual), as well as accounts based only on featural properties (e.g., feature intercorrelations), are insufficient to explain the variability of patients' performance. A first goal of the paper is to discuss how a hybrid account incorporating both a level of organization according to feature types (a level of nonlinguistic conceptual representations) and a level of organization dictated by featural properties may provide a more comprehensive account of the cases reported in the literature. The second and most novel goal of the study reported here is to derive from our hybrid account a series of novel predictions concerning the representation and impairment of a different domain of knowledge: knowledge of actions and events, a domain of knowledge that has received remarkably little attention to date.

Cognition↗
PubMed2000

Anticipation of oxidative damage decelerates aging in virgin female medflies: hypothesis tested by statistical modeling.

Empirical analysis of survival data obtained from large samples of Mediterranean fruit flies shows that the trajectory of the mortality rate for virgin females departs from that for females maintained in mixed sex cages. It increases, decelerates, reaches its maximum, declines and then increases again within the reproductive interval. Non-virgin females, however, display an early-age plateau instead of this dip. We assume that these deviations are produced by the interplay between changes in oxygen consumption associated with reproductive behavior and the antioxidant defense that acts against anticipated oxidative damage caused by reproduction. Since there are no data on antioxidant mechanisms in medflies available that explain the observed patterns of mortality, we develop a model of physiological aging based on oxidative stress theory, which describes age-related changes in oxygen consumption and in antioxidative capacity during the reproductive period. Using this model, we simulate virtual populations of 25,000 virgin and non-virgin flies, calculate the respective mortality rates and show that they practically coincide with those of experimental populations. We show that the hypothesis about the biological support of reproduction used in our model does not contradict experimental data. The model explains how the early-age dip and plateau might arise in the mortality rates of female medflies and why the male mortality pattern does not exhibit such deviations.

Aging↗
PubMed2004

Effects of meteorological factors on epidemic malaria in Ethiopia: a statistical modelling approach based on theoretical reasoning.

This study was conducted to quantify the association between meteorological variables and incidence of Plasmodium falciparum in areas with unstable malaria transmission in Ethiopia. We used morbidity data pertaining to microscopically confirmed cases reported from 35 sites throughout Ethiopia over a period of approximately 6-7 years. A model was developed reflecting biological relationships between meteorological and morbidity variables. A model that included rainfall 2 and 3 months earlier, mean minimum temperature of the previous month and P. falciparum case incidence during the previous month was fitted to morbidity data from the various areas. The model produced similar percentages of over-estimation (19.7% of predictions exceeded twice the observed values) and under-estimation (18.6%, were less than half the observed values). Inclusion of maximum temperature did not improve the model. The model performed better in areas with relatively high or low incidence (>85% of the total variance explained) than those with moderate incidence (55-85% of the total variance explained). The study indicated that a dynamic immunity mechanism is needed in a prediction model. The potential usefulness and drawbacks of the modelling approach in studying the weather-malaria relationship are discussed, including a need for mechanisms that can adequately handle temporal variations in immunity to malaria.

Altitude↗
PubMed1997

Temperature thresholds and statistical modelling of larval Wuchereria bancrofti (Filariidea:Onchocercidae) developmental rates.

Developmental rates for Wuchereria bancrofti larvae maturing in the vector Aedes polynesiensis were estimated by analysing stage-frequency data consisting of counts of larval stages in mosquitoes reared at 20, 22.5, 25, 27.5, 30 and 32 degrees C. Base temperatures (i.e. low temperature thresholds) for W. bancrofti development were estimated by the x-intercept method and the model of Lactin et al. (1995). Resulting values were similar with both methods and were approximately 12.5 degrees C for microfilariae (mf) in thorax, approximately 17 degrees C for L1, 15.5 degrees C for L2 and 16.5 degrees C for L3. Upper thresholds estimated by the Lactin et al. model were 29.3 degrees C for mf, 29.1 degrees C for L1, 32.2 degrees C for L2 and 31.5 degrees C for L3. In addition, an original method was devised for computing the L3 upper threshold, by modelling L3 length shrinkage with temperature. It gave a value of 31.4 degrees C. At 32 degrees C, L2 and L3 stages exhibited altered morphology, larvae being shorter and wider than expected. The model of Lactin et al. described adequately the non-linear relationship between developmental rate and temperature, but a linear degree-day approach may be applied for temperatures below 27-28 degrees C.

Aedes↗
PubMed2006

Time-series analysis of the risk factors for haemorrhagic fever with renal syndrome: comparison of statistical models.

Three conventional regression models were compared using the time-series data of the occurrence of haemorrhagic fever with renal syndrome (HFRS) and several key climatic and occupational variables collected in low-lying land, Anhui Province, China. Model I was a linear time series with normally distributed residuals; model II was a generalized linear model with Poisson-distributed residuals and a log link; and model III was a generalized additive model with the same distributional features as model II. Model I was fitted using least squares whereas models II and III were fitted using maximum likelihood. The results show that the correlations between the HFRS incidence and the independent variables measured (i.e. difference in water level, autumn crop production and density of Apodemus agrarius) ranged from -0.40 to 0.89. The HFRS incidence was positively associated with density of A. agrarius and crop production, but was inversely associated with difference in water level. The residual analyses and the examination of the accuracy of the models indicate that model III may be the most suitable in the assessment of the relationship between the incidence of HFRS and the independent variables.

Animals↗
PubMed2004

Statistical model for large-scale peptide identification in databases from tandem mass spectra using SEQUEST.

Recent technological advances have made multidimensional peptide separation techniques coupled with tandem mass spectrometry the method of choice for high-throughput identification of proteins. Due to these advances, the development of software tools for large-scale, fully automated, unambiguous peptide identification is highly necessary. In this work, we have used as a model the nuclear proteome from Jurkat cells and present a processing algorithm that allows accurate predictions of random matching distributions, based on the two SEQUEST scores Xcorr and DeltaCn. Our method permits a very simple and precise calculation of the probabilities associated with individual peptide assignments, as well as of the false discovery rate among the peptides identified in any experiment. A further mathematical analysis demonstrates that the score distributions are highly dependent on database size and precursor mass window and suggests that the probability associated with SEQUEST scores depends on the number of candidate peptide sequences available for the search. Our results highlight the importance of adjusting the filtering criteria to discriminate between correct and incorrect peptide sequences according to the circumstances of each particular experiment.

Chromatography, Liquid↗
PubMedDate not supplied

A statistical model for predicting protein folding rates from amino acid sequence with structural class information.

Prediction of protein folding rates from amino acid sequences is one of the most important challenges in molecular biology. In this work, I have related the protein folding rates with physical-chemical, energetic and conformational properties of amino acid residues. I found that the classification of proteins into different structural classes shows an excellent correlation between amino acid properties and folding rates of two- and three-state proteins, indicating the importance of native state topology in determining the protein folding rates. I have formulated a simple linear regression model for predicting the protein folding rates from amino acid sequences along with structural class information and obtained an excellent agreement between predicted and experimentally observed folding rates of proteins; the correlation coefficients are 0.99, 0.96 and 0.95, respectively, for all-alpha, all-beta and mixed class proteins. This is the first available method, which is capable of predicting the protein folding rates just from the amino acid sequence with the aid of generic amino acid properties and structural class information.

Amino Acid Sequence↗
PubMed2006

Assessing sites contaminated with unexploded ordnance: statistical modeling of ordnance spatial distribution.

More than 40,000 km2 of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much as 140 billion dollars. The amount of contaminated acreage and total costs are likely to increase as the U.S. Department of Defense (DOD) follows through on recently announced plans to close an additional 22 domestic military bases. The U.S. Environmental Protection Agency(EPA) and DOD disagree on how these sites should be characterized to assess their risks and plan for cleanup. As a result, much potentially valuable land remains idle while remediation decisions are pending. One of the sources of disagreement is how the locations of UXO should be characterized, given that the exact spatial distribution of UXO is unknown in advance of cleanup. In this paper, we propose and test a new model to represent the spatial distribution of UXO. Unlike existing DOD models, the new model accounts for the tendency of UXO to cluster, presumably around targets at which soldiers aimed during training. We fit the cluster model to geographic data on UXO locations at two former military installations and show that it describes key characteristics of the data more accuratelythan the existing DOD model. We discuss how the choice of a UXO spatial distribution model could affect important decisions about cleaning up and reusing UXO-affected property.

Environmental Monitoring↗
PubMed1997

Development of a statistical model for the formation of poly [acryloyl hydroxyethyl starch] microspheres.

PURPOSE: To develop a mathematical model for predicting the molecular weight between crosslinks, Mc, of poly[Acryloyl Hydroxyethyl Starch] (Ac-HES) microspheres system and to identify and evaluate the key microsphere preparation parameters which affect the Mc of the formed microsphere structure based on the developed model. METHODS: Link probability generating functions (LPGFs) based on the classical branching theory were used to derive a model for the calculation of Mc for the Ac-HES system. Based on the developed model, simulation was made to study the effects of the microsphere preparation variables on Mc of the formed microspheres. The process variables were the degree of derivatization (DD) of the Ac-HES, the molar ratio (MR) of the Ac-HES to acrylamide monomer, the fractional conversion of the unsaturation (alpha), the initiator efficiency (f), the molar concentration of initiator (I), the fraction of intramolecular cyclization (c), and the total weight of the reactable monomer and polymer (s). RESULTS: A model to describe the crosslinking reaction of Ac-HES system and predict Mc was developed. Simulation based on the model showed that Mc decreased as alpha increased and reached a limiting value before total conversion. At constant alpha, Mc initially decreased with MR to a minimum and then increased with MR; while Mc decreased monotonically with DD. I and c affected Mc only at very low alpha and changes in s and f had no effect on Mc. CONCLUSIONS: Simulation based on the model suggested that the most important microsphere preparation parameters influencing Mc of the Ac-HES system are the number of functional groups on the Ac-HES (DD) and the stoichiometry (MR) of the crosslinking reaction.

Acrylic Resins↗
PubMed1997

Evaluation of a statistical model for the formation of poly [acryloyl hydroxyethyl starch] microspheres.

PURPOSE: To characterize the network structure of Poly(Acryloyl Hydroxyethyl Starch) (Ac-HES) microspheres and test the theoretical model and the hypothesis that the rate of swelling of microspheres is inversely related to the extent of crosslinking. METHODS: Microspheres were prepared with varying degrees of derivatization (DD) and molar ratios (MR) and subjected to the characterization of matrix structure by dynamic and equilibrium swelling studies utilizing direct microscopic observation and the Flory-Rehner equation. The dependence of average molecular weight between crosslinking Mc, on DD and MR were compared to test the validity of the model. RESULTS: Study of the dependence of Mc on the microspheres preparation parameters, DD and MR, showed that at constant MR, the Mc decreased with DD, while at constant DD, the Mc initially decreased with MR to a minimum, and then increased with MR, complying with the model prediction. Dynamic swelling of microspheres showed a monotonical increase to equilibrium size featured by two time variables, Tp and Teq, that were dependent on Mc; this permitted a conceptual view of the general structure of the Ac-HES microspheres. The Mc, which was more accurately determined by the weight method (as opposed to volume method), was independent of the size of microspheres although there was evidence of variation among particles within a batch. CONCLUSIONS: The results validated the model in describing the polymerization/crosslinking reaction of the Ac-HES microsphere system and suggested that Mc is the principal factor in controlling release.

Acrylic Resins↗
PubMed2002

Including measured genotypes in statistical models to study the interplay of multiple factors affecting complex traits.

The etiology of complex traits may perhaps best be conceptualized by an interplay of multiple factors that mediate the influence of the genes on the eventual outcome. The possibilities of studying aspects of this interplay using existing methods are generally limited. We therefore propose a model with observed and latent variables that does not impose restrictions on the number of variables or the direction of their causal relations and provides a general approach for fitting structural equation models to empirical data. The model is very flexible and (1) allows for genetic effects on the means, variances, and relations between variables, (2) can control for stratification effects on all these components, (3) can be fitted in nuclear families of any size, (4) is estimated using an interpretable parameterization, and (5) can incorporate di- and multi-allelic loci, marker haplotypes, multiple loci simultaneously, and parental genotypes. We indicate how the model can be estimated with the Mx software (Neale et al., 1999) and have written a program to enable geneticists who are not acquainted with Mx to fit their own submodels in a simple and efficient way. A simulation study showed that the model yielded correct Type I errors, unbiased parameter estimates, and satisfactory power to discriminate between alternative models. An example is also given that illustrates how the model could be applied to real data.

Gene Frequency↗
PubMed2001

Statistical model for assessing the proportion of subjects with subjective sensitisations in adverse reactions to foods.

The outcome from a Double-Blind Placebo-Controlled Food Challenge is often of a subjective nature and cannot be measured directly. Reactions to placebo challenges are frequently observed, implying that some of the responses in the study are in fact 'false responses'. In order to adjust for these false responses, previous studies have used various methods, including removing subjects from the analysis who reacted to the placebo. Simply ignoring the false responses can lead to misleading estimates for the true proportion of sensitised individuals. This paper outlines two models which can account for these false responses. In the single challenge study, a simple model is developed which enables the estimation of the rate of false responses in the study, as well as the true proportion of sensitised subjects. This model is very easy to apply in practice. For a repeated challenge study, a more complicated model is developed which again enables the estimation of the rate of false responses and the true proportion of sensitised subjects.

Controlled Clinical Trials as Topic↗