[Non-parametric estimation of the pattern of the age at natural menopause in Garmsar]

Based on WHO, menopause is defined as the permanent cessation of menstruation resulting from the loss of ovarian follicular activity which is recognized to have occurred after 12 consecutive months of amenorrhea, for which there is no other obvious pathological or physiological cause. It is the beginning of a phase of women's' life with somatic and metabolic changes which leads to decrease in quality of life, osteoporosis and heart diseases. Because of increasing the number of women experiencing post-menopausal life, studying the pattern of age in onset of menopause seems necessary. Non-parametric method to estimation the pattern of the age at natural menopause was introduced. For applied purpuses, data from a survey in Garmsar that it is performed on 581 women aged 30 years or older. The pattern of age at menopause was estimated for them using prevalence of menopause in each age group. The mean and median of age at natural menopause were 51.9 +/- 3.6 and 52.2, respectively. Increasing of menopause was slow from age 30 to 43, but a speed-up in monopause was observed until 55 years old, and then it was decreased slowly. compared to the other regions of Iran, the mean of age at natural menopause in Garmsar seems greater

[Sample size determination for matched studies]

One faced to matched data when the main object for a study is investigation of the effect of a given factor on an outcome, such that the samples are matched on the some factors which are known as confounders. The response can be according to quantitative or qualitative scales. Matched case-control, before-after and crossover studies are used frequently in medicine. The significant tests are required to sufficient samples. In this paper, formulas for determination of sample size in matched studies are introduced by considering the scale of response and extended for matched case-control studies with multiple controls and illustrated using practical examples. Using statistical techniques, formulas for determination of sample size are introduced according to the scale of response. The practical examples interpreted in order to clarify the formulas and their applications. One can increase the power and the accuracy of the statistical tests for matched studies, using the introduced formulas

Analyzing receiver operating characteristic curves to compare medical diagnostic tests

One exposes with diagnosis problems when she or he does an experiment or modeling to predict and allocate objects or persons to certain groups. For example in medicine in order to discriminate diabetes or cancers [level 2 of prevention] different criterions or indices can used. The simplest status is allocating objects to two possible categories, therefore one can measure a test variable in ordinal or continuous scale and regarding an appropriate cut-off in range of test variable and sensitivity, specificity and value of loss function, he or she can determine objects for each category. A suitable and single value index to evaluate test variable is A, area under receiver operating characteristic [ROC] curve. Since probably there are several test variables that measured on a unique sample, so there are natural correlations between A's. When one wants to compare and select the best test [s] among them, ignoring of these correlations can lead to confused results. We have detailed a method to compute A's and their variance-covariance matrix and introduced an adequate statistical test to compare them also using a set of simulated data have showed effectiveness of correlations on statistical results. For applied purposes we have prepared a software package using Delphi5. Based on simulated data for two indices we found: A[1] = 0.660, SE[A[1]] = 0.054, A[2] -0.49, SE [A[2]] - 0.06. By ignoring correlations between A[1], A[2] we computed Z =2.1, it leads to reject equality of As in a alpha = 0.05 level, otherwise by regarding correlation, Z =1.92 and equality will accept. Ignoring correlation between As can lead to incorrect results