Logistic Regression in Nursing Practice - Essay Example

The other reasons are difficulty in leaving their job at hand to access healthcare, lack of time to pursue healthcare, vernacular issues and afraid of the medical care system. There have been very few studies which tried to correlate the conditions of US farmworkers that is being related to health care usage. Unfortunately, those studies lacked representativeness of the population and may have some bias associated with it to draw an inference. Thus the goal of this study was to draw fairly a true representative sample from the population of US farmworkers to reduce the component of bias in the statistical interpretations to be made.

On the basis of sampling strategies as discussed, the study selected correlates based on previous literature and the behavioural model for vulnerable populations which imposes the fact the predisposing, enabling, and need characteristics that influence the health care usage. An ecological model was selected to specify the several levels of influence on behaviour, which provided the the overall framework for calculations. Thus the ultimate aim was to find out how each factor relates to health care usage in relation to various factors or correlates and to suggest the interventions needed to improve the health care usage based on these observations.

The Way Regression Equation Is Used Regression equations are used to define the magnitude and direction of relation of one variable with another variable( simple regression) or the relation of a set of variables with another variable.(multiple regression equations like logistic regression equations based on ordinary least squares or linear regression equations). The variable which is studied is called the criterion (dependent variable, in this case the health care usage) and the variable/s on which the dependant variable depends are called the predictor (independent variables, in this case the individual variables, policy variables, ecological variables).

Therefore in this study the Health care usage was correlated in the equation by bivariate models and multivariate models. Bivariate means predicting the health care usage depending upon another variable with which health care is correlated. In multivariate logistic regression model the health care usage was predicted holistically depending upon two or more variables because in bivariate model only one independent variable is considered. In multivariate logistic model many variables at a single time in relation to each other and health care usage can be evaluated which gives a more realistic view to the situation because individual variables, behavioural variables, ecological variables are all related to each other to finally impact health care usage.

In other words the multiple regression equations provide a logical and at once glance of the weighted impact of all the independent variables on the dependent variable ( in this case health care usage pattern). In logistic equations the important aspect is to evaluate the correlation coefficients which means how a variable is related to other that is whether increase in the value of one will increase or decrease the magnitude of another variable. This coefficient called product moment correlation(r) has a value from -1 to +1.

This means more the positive magnitude more the increase in magnitude of one variable will increase the