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At least 919 records · Page 51Linked to original sources
PubMed2002

A three-dimensional model for the tooth-loss patterns by multi-plane regression analysis.

The construction of dental condition models is one of the useful methods for analysis of epidemiological surveys. The purpose of this investigation was to make a simple model with clear turning points for the longitudinal tooth-loss patterns of Japanese adults by means of multi-plane regression analysis. Since 1957, the Japanese Ministry of Health and Welfare has carried out national surveys of dental conditions every six years. The data of present tooth numbers by age (24-79 years) and sex from these surveys were used for this study. When there are turning points between two variables, intersecting straight lines regression is a valid means. However, a new method was developed so that the data of this study had three variables. The new three-dimensional model by multi-plane regression analysis seemed to fit tooth-loss patterns of Japanese adults within three phases. Younger subjects are represented in the first phase followed by the third phase of elders, where tooth loss was rather slow. However, in the second phase, middle-aged subjects, people lost their teeth rapidly. Thus, prolongation of the first phase could be an important factor to improve overall dental health.

Adult↗
PubMed1999

Approximate standard errors in semiparametric models.

We consider semiparametric models with p regressor terms and q smooth terms. We obtain an explicit expression for the estimate of the regression coefficients given by the back-fitting algorithm. The calculation of the standard errors of these estimates based on this expression is a considerable computational exercise. We present an alternative, approximate method of calculation that is less demanding. With smoothing splines, the method is exact, while with loess, it gives good estimates of standard errors. We assess the adequacy of our approximation and of another approximation with the help of two examples.

Agriculture↗
PubMed1992

Multiple correlates of cigarette use among high school students.

A cross-sectional survey research design measured factors related to cigarette use among 2,212 senior high school students. Results showed 14.3% of the sample smoked cigarettes at least occasionally, with 5.3% reporting they were daily smokers. About 12.8% indicated they were ex-smokers. Males and females smoked at almost equal rates, and the percentage of 10th grade student smokers was slightly higher (16.4%) than the percentage of juniors and seniors who smoked. Approximately 22% of Hispanic students, 15% of Caucasian students, and 4.5% of African-American students reported smoking cigarettes at least occasionally. An initial regression analysis used 21 variables to predict cigarette smoking. A more parsimonious regression model (R2 = .28), using variables from the initial regression analysis with significance levels of .01 or less, indicated the most important predictors of cigarette use were ethnic group, attitude toward females who smoke, close friends' use of cigarettes, personal use of marijuana, best friend's use of cigarettes, personal use of alcohol, and school self-esteem. Implications for school health programs are addressed.

Adolescent↗
PubMed1992

Efficacy of repeated measures in regression models with measurement error.

Ignoring measurement error may cause bias in the estimation of regression parameters. When the true covariates are unobservable, multiple imprecise measurements can be used in the analysis to correct for the associated bias. We suggest a simple estimating procedure that gives consistent estimates of regression parameters by using the repeated measurements with error. The relative Pitman efficiency of our estimator based on models with and without measurement error has been found to be a simple function of the number of replicates and the ratio of intra- to inter-variance of the true covariate. The procedure thus provides a guide for deciding the number of repeated measurements in the design stage. An example from a survey study is presented.

Biometry↗
PubMed1990

Assessing proportionality in the proportional odds model for ordinal logistic regression.

The proportional odds model for ordinal logistic regression provides a useful extension of the binary logistic model to situations where the response variable takes on values in a set of ordered categories. The model may be represented by a series of logistic regressions for dependent binary variables, with common regression parameters reflecting the proportional odds assumption. Key to the valid application of the model is the assessment of the proportionality assumption. An approach is described arising from comparisons of the separate (correlated) fits to the binary logistic models underlying the overall model. Based on asymptotic distributional results, formal goodness-of-fit measures are constructed to supplement informal comparisons of the different fits. A number of proposals, including application of bootstrap simulation, are discussed and illustrated with a data example.

Biometry↗
PubMed1998

Regression equations in clinical neuropsychology: an evaluation of statistical methods for comparing predicted and obtained scores.

Regression equations are widely used in clinical neuropsychology, particularly as an alternative to conventional normative data. In neuropsychological applications the most common method of making inferences concerning the difference between an individual's test score and the score predicted by a regression equation is to multiply the standard error of estimate by an appropriate value of z to form confidence limits around the predicted score. The technically correct method is to calculate the standard error of a new individual Y and multiply it by the value of t corresponding to the desired limits (e.g., 90% or 95%). These two methods are compared in data sets generated to be broadly representative of data sets used in clinical neuropsychology. The former method produces confidence limits which are narrower than the true confidence limits and fail to reflect the fact that limits become wider as scores on the predictor deviate from the mean. However, for many of the example data sets studied, the differences between the two methods were trivial, thereby providing reassurance for those who use the former (technically incorrect) method. Despite this, it would be preferable to use the correct method particularly with equations derived from samples with modest Ns, and for individuals with extreme scores on the predictor variable(s). To facilitate use of the correct method a computer program is made available for clinical practice.

Algorithms↗
PubMed1992

Alcohol consumption regression models for distinguishing between beverage type effects and beverage preference effects.

In relating health outcomes to alcohol consumption, several investigators have evaluated differences among beverage types, but there is no consistency with respect to models used for this purpose. Furthermore, beverage type effects and beverage preference effects have not been evaluated simultaneously. In this report, the authors propose regression models which permit the simultaneous evaluation of beverage type (congener dose response) effects and beverage preference (sociobehavioral) effects. The presence of sociobehavioral effects can be established even if the variables responsible for them have not been measured or identified. The models are applied to a data set from 589 women who participated in an oral contraceptive study at the Johns Hopkins University (Baltimore, Maryland) in 1988-1989.

Adolescent↗
PubMed2001

Sensitivity and specificity of serum copper determination for detection of copper deficiency in feeder calves.

OBJECTIVE: To determine the relationship between serum and liver copper concentrations and evaluate serum copper determination for diagnosis of copper deficiency in juvenile beef calves. DESIGN: Cross-sectional study. ANIMALS: 105 juvenile beef calves. PROCEDURE: Copper concentrations were measured in paired liver and serum samples from 6- to 9-month-old beef calves. Regression models that predicted liver copper concentration as a function of serum copper concentration were developed. Sensitivity and specificity of serum copper concentration for detection of low liver copper concentration were determined, using a range of serum copper concentrations as test endpoints. Positive and negative predictive values were calculated. RESULTS: The association between serum and liver copper concentrations was significant; however, regression models accounted for only a small portion of the variation in liver copper concentrations. For a serum copper concentration endpoint of 0.45 microg/g, sensitivity and specificity for detection of low liver copper concentration were 0.53 and 0.89, respectively. Positive and negative predictive values of serum copper concentration for detection of low liver copper concentration ranged from 0.37 to 0.85 and 0.63 to 0.94, respectively. CONCLUSIONS AND CLINICAL RELEVANCE: Regression models are inappropriate for predicting copper status as a function of serum copper concentration. Serum copper concentration is fairly specific for detection of low liver copper concentration but only marginally sensitive when serum copper concentration of 0.45 microg/g is used as a test endpoint. The value of serum copper concentration as a diagnostic indicator depends on prevalence of copper deficiency.

Animals↗
PubMed1989

A state-based regression model for estimating substate life expectancy.

Life expectancy is an important indicator of the level of mortality in a population. However, the conventional way of calculating life expectancy--constructing a life table--has rigorous data requirements. As a consequence, life expectancy data are not usually available for substate areas. In this article, a regression model for estimating life expectancy is constructed, using state-level data, and is tested against two sets of 1980 life expectancy data: (1) a nationwide sample of metropolitan areas and (2) selected cities, their suburbs, and rural counties in Ohio. An additional test shows the sensitivity of the model's accuracy to errors in one of its input data elements. The results suggest that the model should be given serious consideration for generating life expectancy estimates for substate areas.

Demography↗
PubMed1990

Zinc in breast milk during prolonged lactation: comparison between the UK and the Gambia.

A total of 580 breast milk samples were collected from 56 lactating women living in a rural village community in The Gambia, West Africa, and 92 samples were obtained from 57 lactating women living in Cambridge, England. Total zinc content of each sample was measured by atomic absorption spectrometry, and pooled samples of the Gambian breast milks, representing successive periods of lactation, were fractionated into fat, whey and insoluble casein fractions, to examine zinc distribution. The two sets of milks both exhibited a dramatic decline in total zinc concentrations with increasing duration of lactation, in common with previous studies. However, the UK milks unexpectedly had lower zinc contents at all stages than the Gambian milks. Milk zinc levels were not significantly related to either maternal age or parity in the Gambian women. The proportion of zinc found in the sedimentable fraction remained nearly constant with increasing duration of lactation, but the proportion found in the fat fraction increased and the proportion in the whey fraction declined. These observations are potentially relevant for estimations of milk zinc availability and the fulfillment of zinc requirements by infants, and hence for infant feeding practices.

Adolescent↗
PubMed1988

Multivariate approaches to the identification of delinquency proneness in adolescent males.

A sample of 337 adolescent male students were surveyed for demographic, individual, school, and familial functioning and delinquency status to investigate two questions relevant to prediction of adolescent delinquency proneness. First, three methods of scoring a delinquency self-report measure (frequency, variety, and seriousness) were compared to assess their differential relevance to the prediction of delinquency proneness. Second, a multivariate model was examined to assess its explanatory ability for identification of delinquency proneness. Findings, replicated through a series of regression analyses, demonstrate that age of onset is the best predictor. Other than family functioning, psychosocial indicators add little to the predictive model. Third, a specific factor model was preferable to a "risk count" method. Finally, the advantage of self-reports of delinquent behavior over official records is discussed as is the comparability of self-report scoring procedures. How self-reported delinquency is scored is not as critical as previously thought.

Achievement↗
PubMed1991

Conversion factor instability in international comparisons of health care expenditure.

Parkin, McGuire and Yule (1987) (hereafter PMY) report that a regression of per capita health care expenditure on per capita income using different conversion factors (exchange rates, GDP PPPs, health PPPs) gave rise to different results. In this note we apply updated data to the same empirical relationship. In contrast to PMY, we find no noticeable conversion factor instability in that relationship either with respect to the health care income elasticity or with the magnitude of multiple correlation coefficient.

Costs and Cost Analysis↗
PubMed2004

A meta-analysis examining the relationship among dietary factors, dry matter intake, and milk and milk protein yield in dairy cows.

This meta-analysis was undertaken to determine the impact of dietary components on dry matter intake (DMI), milk yield (MY), and milk protein yield (MPY) in Holstein dairy cows. Diets (n=846) from 256 feeding trials published in Volumes 73 through 83 of the Journal of Dairy Science were evaluated for nutrient composition using 2 diet evaluation models: CPM Dairy (a computer program based on the principles of the Cornell Net Carbohydrate and Protein System) and NRC (2001). Data were analyzed with and without the effect of stage of lactation as a dummy variable (<100 d in milk or > or =100 d in milk). A mixed model regression analysis was used to completely investigate the potential relationships among composition variables and DMI, MY, and MPY. Protein and carbohydrate fractions were the main components within the DMI models, and DMI played a dominant role in estimating MY and MPY. Inclusion of stage of lactation substantially improved the MY models but did not affect model fits or residual structure for DMI and MPY.

Animal Feed↗
PubMed2006

Evaluation of four modelling techniques to predict the potential distribution of ticks using indigenous cattle infestations as calibration data.

Efficient tick and tick-borne disease control is a major goal in the efforts to improve the livestock industry in developing countries. To gain a better understanding of the distribution and abundance of livestock ticks under changing environmental conditions, a country-wide field survey of tick infestations on indigenous cattle was recently carried out in Tanzania. This paper evaluates four models to generate tick predictive maps including areas between the localities that were surveyed. Four techniques were compared: (1) linear discriminant analysis, (2) quadratic discriminant analysis, (3) generalised regression analysis, and (4) the weights-of-evidence method. Inter-model comparison was accomplished with a data-set of adult Rhipicephalus appendiculatus ticks and a set of predictor variables covering monthly mean temperature, relative humidity, rainfall, and the normalised difference vegetation index (NDVI). The data-set of tick records was divided into two equal subsets one of which was utilised for model fitting and the other for evaluation, and vice versa, in two independent experiments. For each locality the probability of tick occurrence was predicted and compared with the proportion of infested animals observed in the field; overall predictive success was measured with mean squared difference (MSD). All models exhibited a relatively good performance in configurations with optimised sets of predictors. The linear discriminant model had the least predictive success (MSD>or=0.210), whereas the accuracy increased in the quadratic discriminant (MSD>or=0.197) and generalised regression models (MSD>or=0.173). The best predictions were gained with the weights-of-evidence model (MSD>or=0.141). Theoretical as well as practical aspects of all models were taken into account. In summary, the weights-of-evidence model was considered to be the best option for the purpose of predictive mapping of the risk of infestation of Tanzanian indigenous cattle. A detailed description of the implementation of this model is provided in an annex to this paper.

Animals↗
PubMed1992

Menstrual function after tubal sterilization.

More than 10 million women in the United States have undergone tubal sterilization. There has been concern that this procedure may increase the risk of later menstrual dysfunction. The Collaborative Review of Sterilization (CREST) is a large, multicenter, prospective study of tubal sterilization in the United States. This report describes CREST participants who were interviewed immediately before sterilization and again in annual poststerilization interviews for up to 5 years between 1978 and 1988. The authors analyzed reported changes in six menstrual cycle characteristics for 5,070 women undergoing interval sterilizations. Longitudinal, multivariate regression was used to adjust for baseline menstrual function and other potential confounders. Five years after sterilization, 35% of the CREST participants reported high levels of menstrual pain, 49% reported heavy or very heavy menstrual flow, and 10% reported spotting between periods. In contrast to the fifth year, the first year of follow-up was similar to presterilization menstrual function; in the first year, 27% of participants reported high menstrual pain, 41% reported heavy menstrual flow, and 7% reported spotting. These findings may be affected by aging of the cohort and other study limitations, but they suggest that if tubal sterilization leads to changes in menstrual function, such changes may take some time to develop.

Adolescent↗
PubMed1995

Neurological recovery, mortality and length of stay after acute spinal cord injury associated with changes in management.

Based on epidemiological data from two populations of patients with acute spinal cord injury (ASCI), three outcome measures were compared to evaluate the effectiveness of management of ASCI patients in a regional, specialized acute spinal cord injury unit (ASCIU). The two populations consisted of a pre-ASCIU group of 351 patients managed from 1947-73 before the establishment of the ASCIU, and an ASCIU group of 201 patients managed in an ASCIU from 1974-81. The three outcome measures were mortality rate, length of stay (LOS) during first hospitalization, and neurological recovery. Linear regression and multiple regression analyses were used to determine whether differences in the outcome measures were attributable to differences in admission variables in addition to the influence of the ASCIU. The results showed that the patients treated in the ASCIU had a significant reduction in the mortality rate of almost 50% (P = 0.022), a significant reduction in the LOS of almost 50% (P < 0.001), and a significant increase in neurological recovery consisting of a doubling of the neurological recovery scale utilized (P < 0.001). Multiple regression analysis showed that the reduction in mortality rate was significantly influenced by differences in the admission variables between the two groups. However, the establishment of the ASCIU was associated with a significant reduction in LOS and a significant improvement in neurological recovery. Thus, these results support the view that management of ASCI patients in a regional, multidisciplinary unit is medically advantageous and can reduce the LOS.

Acute Disease↗
PubMed1992

Patterns and predictors of high-risk sexual behavior in female partners of HIV-infected men with hemophilia.

OBJECTIVE: To characterize and quantify high-risk heterosexual activity in HIV-discordant couples. DESIGN: Analysis of cross-sectional and longitudinal questionnaire data from 217 HIV-negative female sexual partners of HIV-infected hemophilic men. METHODS: Comparison of prevalence rates of anal sex, oral sex, vaginal intercourse with or without condoms, and use of other contraceptives between 1985 and 1991. Logistic regression analysis of demographic, sexual and clinical variables to predict unprotected vaginal sex. Actuarial estimates of semi-annual relapse rates to unsafe sex. RESULTS: The proportion of women at low risk increased from 7 to 69% between 1985 and 1991, mainly because more women were using condoms during all acts of vaginal intercourse. Other contraceptive practices did not change during this time. The proportion engaging in oral or anal sex decreased (from 26 to 13% and 13 to 4%, respectively). Unprotected vaginal sex was more common among women who enrolled earlier, had less education, engaged in oral or anal sex, and among those whose partners had not had AIDS. Unprotected vaginal sex before enrollment was the strongest predictor of this high-risk activity during follow-up. Two-year rates of relapse to high-risk behavior were significantly higher among women who enrolled at high risk compared with those who enrolled at low risk (39 versus 8%, P = 0.005). CONCLUSIONS: Although high-risk sexual behavior became much less prevalent in this population between 1985 and 1991, many continued to have unprotected vaginal sex occasionally. Counseling efforts should target couples who have been the most sexually active or have less education, and should emphasize not only initial risk reduction but also maintenance of low-risk behavior.

Adolescent↗