Statistical Analysis in Nursing Essay Example | Topics and Well Written Essays - 1250 words

Statistical Analysis in Nursing - Essay Example 2.Non parametric tests like Chi square tests and Fischer’s test (as used in this study) are used when the sample size is small and does not represent the population in totality and also when the variables are ordinal, nominal and discrete variables( variables which cannot be measured and even if measured cannot be extrapolated to decimal places). Chi square value evaluates the association or independence between the two variables. If the probability value (p value) for null hypothesis for a particular value of chi square exceeds the critical chi square value then it is inferred that the two variables are not independent and the two variables are significantly associated with each other. ... ean importance values for each factor for the group of 21 nurses studied which were likely to influence decision making patterns were- future health status, 39%; family input, 19%; person's age, 13%; extra cost to agency, 12%; functional status, 10%; and mental competence, 6%. There were three other decision-making patterns, each exhibited by one nurse: One nurse relied heavily on mental competence (43%) and person's age (52%), another emphasized mental competence (43%) and functional status (29%), and the third used extra cost to agency (66%) supplemented by person's age (18%) for treatment of ID. Nurse's work site, age, education, and years of experience did not discriminate among these decision making patterns in this small pilot study sample.(These factors were not associated or correlated with decision making ) 3. Parametric tests like Student’s t test and ANOVA wee not suitable for this study as because the variables in question were not quantitative variables(measuremen t variables) and also because the sample size was too small. 4. The strengths of the study was rather than a prescriptive or normative perspective on decision making the method revealed how actually a decision making happens in a real life simulated situation. The measurements were appropriate in relation to chi square, Pearson’s r and Fischer’s test considering small and non-representative sample of the total population. The study design included all the appropriate variables that could have affected decision making process. The limitations were the sample size which needed to be more to have a correct extrapolation to the ID population treated at the ED on totality. Real-world decision making may depart from what was found in this study because simulation provides only an approximation of