The high population growth rate can impact various fields due to several factors. Some of the impacts this are poverty rates, unemployment, consumption levels, inequality in education figures, gender empowerment index, and increasingly narrow land or area. Therefore, research on using data poverty, area makes sense. This was taken from official website Central Statistics Agency for six province...

The ability to simulate correlated binary data is important for sample size calculation and comparison of methods for analysis of clustered and longitudinal data with dichotomous outcomes. One available approach for simulating length n vectors of dichotomous random variables is to sample from the multinomial distribution of all possible length n permutations of zeros and ones. However, the mult...

BACKGROUND A sample size containing at least 100 events and 100 non-events has been suggested to validate a predictive model, regardless of the model being validated and that certain factors can influence calibration of the predictive model (discrimination, parameterization and incidence). Scoring systems based on binary logistic regression models are a specific type of predictive model. OBJE...

The medical studies often require different methods for parameters selection, as a second step of processing, after the database’s designing and filling with information. One common task is the selection of fields that act as risk factors using wellknown methods, in order to find the most relevant risk factors and to establish a possible hierarchy between them. Different methods are available i...

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Se...

Let Y be a binary random variable and X a scalar. Let β̂ be the maximum likelihood estimate of the slope in a logistic regression of Y on X with intercept. Further let x̄0 and x̄1 be the average of sample x values for cases with y = 0 and y = 1, respectively. Then under a condition that rules out separable predictors, we show that sign(β̂) = sign(x̄1− x̄0). More generally, if xi are vector valued the...