Webmedcentral - Biostatistics ArticlesThe Biostatistics articles published by Webmedcentral
http://www.webmedcentral.com
2019-08-26T09:23:28+01:00webmedcentral logo
http://www.webmedcentral.com/
http://www.webmedcentral.com/images/Header_Logo.giftext/html2012-05-05T12:12:52+01:00http://www.webmedcentral.com/Dr. Brijesh SathianImportance of Biostatistics to Improve the Quality of Medical Journals
http://www.webmedcentral.com/article_view/3332
Most of the Medical journals are facing the methodological rigor problem. A p value of &lt;0.05 means that this result would have arisen by chance on less than five occasion in 100. The confidence interval around a result in a clinical trial indicates the limits within which the “real” difference between the treatments is likely to lie, and hence the strength of the inference that can be drawn from the result. A statistically significant result may not be clinically significant. Many researchers are not giving due importance to optimum size calculation, confidence intervals and testing of hypothesis while undertaking their research. This negligence results in wrong conclusions and thus reducing the quality of their research. Absence of evidence is not evidence of absence. Medical researcher should follow the tenets of biostatistics and the suggestions of a qualified biostatistician even from the stage of conceptualization to the finality of publication of the work. text/html2011-09-06T14:15:26+01:00http://www.webmedcentral.com/Dr. Marina SapirSmooth Rank: A Method for Robust Risk Modeling for Smaller Samples
http://www.webmedcentral.com/article_view/2167
Prognosis of disease progression is necessary for development of individualized treatment, understanding of the disease. Risk modeling is a challenging problem, and too often amount of available relevant observations is not sufficient to build a quality model with traditional approaches.New method Smooth Rank for survival analysis, risk modeling is introduced here. Smooth Rank is robust against overfitting on relatively small samples. The method is compared with established risk modeling methods on 10 real life datasets. The experiments confirmed significant advantage of the proposed method on smaller samples.text/html2012-05-07T16:24:51+01:00http://www.webmedcentral.com/Dr. Brijesh SathianStatistical Methods for Modeling HIV/AIDS in India
http://www.webmedcentral.com/article_view/3336
Deterministic, Stochastic, Statistical and State space models are the statistical models for forecasting HIV/ AIDS data. There are also uncertainties associated with these approaches. In addition to this the recent advance in this field used is curve fitting models. Sathian B and Sreedharan J used this method for forecasting several infectious and non infectious diseases. It gives more accurate estimates compared to the other models.text/html2012-05-07T16:21:33+01:00http://www.webmedcentral.com/Dr. Brijesh SathianMeaning of p-value in Medical Research
http://www.webmedcentral.com/article_view/3338
Any researcher begins the research with null hypothesis and alternative hypothesis. Null will be for supporting the old fact and alternative will be for the new fact invented/ doubted by the researcher/ scientist. Next step is to select one of this scientifically by using the science of statistics. For that the researcher should calculate the likelihood or probability that the difference observed in the study, however big or small, could have arisen purely by chance. This probability is known as p-value and it is sufficiently small, you can conclude that you have obtained a statistically significant difference. Confidence intervals and p-values take as their starting point the results observed in a study. Crucially, we must check first that this is an unbiased study.text/html2011-02-23T18:40:44+01:00http://www.webmedcentral.com/Dr. Shivalingappa B JavaliEffect Of Varying Sample Size In Estimation Of Reliability Coefficients Of Internal Consistency
http://www.webmedcentral.com/article_view/1572
Reliability refers to accuracy and precision of a measurement instrument or scale. Reliability of test scores are estimated through measures of internal consistency has been characterized mathematically in many ways that appear, on the surface at least, to be very different to one another. The coefficient alpha is the most widely used measure of internal consistency for composite scores. In this article, the inferential statistics for three coefficients of internal consistency i.e. alpha coefficient with theta coefficient and omega coefficients are estimated. These indices of reliability are extremely important in health research (medical and oral health). The estimation of alpha, theta and omega coefficients and analytical effects under different sample sizes are examined and described. But computations of these coefficients are easily put forwarded by statistical software programs like SPSS, STATA, SYSTAT, STATISTICA etc. The good quantity of reliability estimates is observed in the sample size of 50 and more. Therefore, the researcher claims that for calculation of reliability coefficient for five points scale or any, the sample size should be at least 50 and more is enough. It is also concluded that with a prescription that every time a researcher reports any one of alpha coefficient, theta coefficient and omega coefficients.text/html2011-02-28T18:50:43+01:00http://www.webmedcentral.com/Dr. Shivalingappa B JavaliEffect of Varying Sample Size in Estimation of Coefficients of Internal Consistency
http://www.webmedcentral.com/article_view/1649
Reliability refers to accuracy of a measurement instrument or scale. Reliability of test scores are estimated through measures of internal consistency has been characterized mathematically in many ways that appear, on the surface at least, to be very different to one another. The coefficient alpha is the most widely used measure of internal consistency for composite scores. In this article, the inferential statistics for three coefficients of internal consistency i.e. alpha coefficient with theta coefficient and omega coefficients are estimated. These indices of internal consistency reliability are extremely important in health research (medical and oral health). The estimation of alpha, theta and omega coefficients and analytical effects under different sample sizes are examined and described. But computations of these coefficients are easily put forwarded by statistical software programs like SPSS, STATA, SYSTAT, STATISTICA etc. The good quantity of internal consistency estimates is observed in the sample size of 50 and more. Therefore, the researcher claims that for calculation of coefficient of internal consistency for five points scale or any, the sample size should be at least 50 and more is enough. It is also concluded that with a prescription that every time a researcher reports any one of alpha coefficient, theta coefficient and omega coefficients.text/html2011-03-07T18:20:42+01:00http://www.webmedcentral.com/Dr. Shivalingappa B JavaliA Structural Equation Model of the Determinants of Health Care in the Surveyed Households in Rural of Dharwad District, Karnataka State, India
http://www.webmedcentral.com/article_view/1698
Purpose: To examine the causal relationships among factors determining how much care people are willing to purchase.Method: A systematic random sample of 1408 persons interviewed from 320 households,in which 418 persons were reported with health problems.Out of this 235 persons were reported with medical health problems and 218 persons were reported with oral health problems during reference period of study.The data on different factors were collected through direct personal interview method. The causal relationships were established by structural equation modeling (SEM) method using SPSS and AMOS statistical software.Results: The SEM fitted to the medical and oral health care data adequately.The results indicated that, the age of sick person, duration of illness episode (in days) and the total number of visits made to source of health care during the reference period had significant effect on medical health care expenditure (pConclusions: The duration of illness episode (in days) and the total number of visits made to source of health care during the reference period are the main contributors to both medical and oral health care expenditure in surveyed households in rural of Dharwad district, Karnataka State, India. It is proposed that to increase in the demand for health care, efforts should be made to reduce the duration of illness, the distance traveled by the sick person or patient and also the number of visits to health care providers. It may lead to improved health status at lower expenditure.