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At least 631 records · Page 35Linked to original sources
PubMed1995

Regression analysis of factorially designed trials--a logical approach to protein crystallization.

The specific composition of the mother liquor that induces the formation of protein crystal is usually quoted as the 'best condition' for crystallization. However, very little is described about how these conditions were determined. These missing and non-reported details would certainly lead to a better understanding of why a specific purified protein does not crystallize, and why crystallization seems to be a totally unpredictable enterprise. In this paper, it is shown that a simple regression model applied to a set of factorially designed experiments (comprising successful and failed experiments) is a useful tool for the analysis of crystallization outcomes. The applications of this approach to the proteins lysozyme and calmodulin yielded results that did not substantially differ from published accounts. When this procedure is applied to myelin basic protein (MBP) and to a MBP and calmodulin complex no crystals formed, which would suggest that neither is easy to crystallize. In summary, factorial design and regression analysis can be an important methodological approach for crystallizing proteins.

Calmodulin↗
PubMed1990

Use of regression analysis in reconstruction of maximum bone length and living stature from fragmentary measures of the ulna.

The present study deals with the computation of linear and multilinear regression formulae for reconstruction of ulnar length and stature through eleven fregmentary measures pertaining to linear, transverse, sagittal and circumferential dimensions of the ulna bone. A total of 288 ulnae, belonging to 82 male and 62 female documented skeletons have been measured for this purpose. The data reveals a non-significant bilateral variation in the fragmentary measures of the ulna while the sex differences are highly significant at 1% level. Keeping this in view, separate regression equations have been formulated for both the sexes. The study further highlights that the upper shaft circumference is the best predictor of ulnar length among all the fragmentary measures while stature can best be reconstructed using the breadth of olecranon. However, the maximum length as a non-fragmentary measure provides the most accurate estimate. In order to increase the accuracy in prediction of ulnar length and stature, multiple regression equations have also be constructed and used.

Adult↗
PubMed2000

Sample size and multiple regression analysis.

Despite the development of procedures for calculating sample size as a function of relevant effect size parameters, rules of thumb tend to persist in designs of multiple regression studies. One explanation for their persistence may be the difficulty in formulating a reasonable a priori value of an effect size to be detected. This article presents methods for calculating effect sizes in multiple regression from a variety of perspectives and also introduces a new method based on an exchangeability structure among predictor variables. No single method is deemed superior, but rather examples show that a combination of methods is likely to be most valuable in many situations. A simulation provides a 2nd explanation for why rules of thumb for choosing sample size have persisted but also shows that the outcome of such underpowered studies will be a literature consisting of seemingly contradictory results.

Child↗
PubMed1998

Hospital mortality after urgent and emergency laparotomy in patients aged 65 yr and over. Risk and prediction of risk using multiple logistic regression analysis.

We studied 107 patients aged over 65 years undergoing urgent or emergency laparotomy. Aspects of preoperative assessment, perioperative management and postoperative care were analysed by multiple logistic regression to determine the factors that predicted hospital survival. We determined which factors influenced anaesthetists' prediction that patients would survive. These predictions were made both before and immediately after operation. The factors associated with the use of invasive cardiovascular monitoring were also studied. We obtained a model that accounted for 93% of the variability in the likelihood of survival. Age and ASA status were significant predictors of survival (P < 0.05), and of anaesthetists' prediction of mortality both before and after operation. Several other factors were significant determinants of survival but were not determinants of the anaesthetist's opinion regarding survival.

Aged↗
PubMed1978

Factors predicing survival after portacaval shunt: a multiple linear regression analysis.

The predictive value of 15 pre- and peroperative parameters upon survival after portacaval shunt was analyzed in a retrospective investigation of 134 elective operations. A multiple linear regression model was used. Survival was measured at three different points of time: one month, one year and five years after the operation. Survival at one month was influenced by the parameters bilirubin/s and ascites only. Survival at one year was influenced by albumin/s, sex, bilirubin/s, BSP, heart disease history and ascites Survival at five years was influenced by albumin/s, alkaline phosphatase/s, history of alcohol abuse, and globulin/s. These findings indicate that prediction of survival after portacaval shunt is an intricate process and that considerable improvement of the child criteria is possible.

Female↗
PubMed1997

Sensitization to dust mites as a dominant risk factor for asthma among adolescents living in central Virginia. Multiple regression analysis of a population-based study.

Factors influencing asthma were investigated in a population of school children in central Virginia. A survey of 1,054 children in two middle schools (one urban and one suburban) identified 135 students with symptoms suggestive of asthma. Eighty-eight symptomatic children and 123 control subjects were randomly selected for further evaluation by skin testing using common indoor and outdoor allergens; serum assays for total IgE and specific IgE; dust samples assayed for mite (Der p 1 Der f 1), cat (Fel d 1), and cockroach (Bla g 2) allergens; and provocation with histamine to test for bronchial hyperreactivity. Forty-eight of the children with symptoms responded to < or = 3.9 mumol of histamine and were considered to have asthma. Marginal analysis identified elevated total IgE and dust mite, cat, and cockroach sensitization as significant risk factors for asthma. Using multiple regression, only dust mite sensitization was independently associated with asthma (odds ratio = 6.6; p < 0.0001). Dust from 81% of the houses contained high levels of mite allergen (> 2 micrograms/g), while approximately 40% of the children were exposed to cat and 17% were exposed to cockroach allergen. In this population, there was no significant association between asthma and race, socioeconomic status, home smoking, sensitization to outdoor allergens, or allergen concentration in the child's home. In an area where there is a high prevalence of asthma and most houses contain high concentrations of dust mite allergen, sensitization to this allergen is the dominant risk factor for asthma defined as symptomatic bronchial hyperreactivity

Adolescent↗
PubMedDate not supplied

Possibilities of the application of regression analysis and analysis of variance. II. Assessment and comparison of acute toxicity: presentation and practical application of the interactive computer program "LD50-MORTALITY".

The paper presents the interactive computer program "LD50-MORTALITY", written in the program language BASIC and used for the assessment of the acute toxicity (calculation of LD50 and other LD values) based on the algorithm of the Finney's probit analysis method. The correctness of the program execution has been shown on the test-example of assessment the acute toxicity (LD50 an LD90) of insecticide rotenone on Macrosiphonelia sanborni (the example is taken from the literature on probit analysis presentation). The results obtained by the program execution have been identical or similar to those given in the example. The results of the assessment and comparison of LD50 have also been presented.

Algorithms↗
PubMed1993

Regression analysis of grouped survival data: informative censoring and double sampling.

To analyze grouped survival data subject to informative censoring, we propose the following two-part model: a logistic regression model for the hazard for failure, given covariates and a logistic regression model for the hazard for informative censoring, given time of failure and covariates. We fit the model to survival data arising from a double sampling design: In a full follow-up (FF) sample subjects are followed after censoring, and in a partial follow-up (PF) sample subjects are not followed after censoring. We illustrate the methodology using data from a study of wound infection in which patients in the PF sample are censored by release from the hospital, whereas patients in the FF sample are followed after hospital release. We discuss identifiability when there is only a PF sample. We also consider how the allocation between the PF and FF samples affects the precision of estimates.

Follow-Up Studies↗