Question

NOTE: this is a nursing research question and needs to be answered in a generalized aspect.

1. How do inclusion and exclusion criteria contribute to increasing the strength of evidence of the sampling strategy in a research study?

2. Why is it important for a researcher to use power analysis to calculate sample size?

3. How does an adequate sample size affect the following: a) subject mortality, b) representativeness of the sample, c) the researcher's ability to detect a treatment effect, and d) your ability to generalize the study findings to your patient population?

Answer 1

1.

The inclusion and exclusion criteria plays impotant role in the research. The inclusion criteria says about who are going to include in our study, what specific characterstics of the subject are needed in the study etc. And the exclusion criteria represents that who are excluded from the study, future study topic, etc.

Yes, the inclusion and exclusion criteria are going to increase the strength of evidence of the sampling strategy. The study sample generally depends upon the inclusion and exclusion criteria. In some studies relating to drugs they manifests that the pregnant women are excluded from the study. These represent that the drug may be harmful to the patient or they are not taking any risks.

In some other studies they do not include geriatrics and pediatrics in the study due to high risk complications and untolerable doses etc.

2.

It is very impotant for a researcher to calculate sample size by using power analysis. Power analysis is a statistical method. It calculates the sample size depending upon the requirements we have, effect and subject area knoledge. It is very inportant to detect sample size for a study because improper sample size can leads to error or wrong results. If you want to know only few effects then sample sample size is enough. If the effects are more then we require large sample size to get accurate results. The sample selection for a study is toughest process and large sample size also requires al lot of money. So it is important to use statistical methods to estimate the sample size. before using the power analysis we have to know what data to be collected, how to collect it, who are going to collect the data, from whom the data is collected. If the enetered data is accurate then we can get accurate hypothesis. By using hypothesis testing we can calculate the p value of the study.

The software asks about the difference, power values and standard deviation. Take the help of experts before deciding power values. Generally these power values are 0.8 & 0.9. After entering all the values in specified software we can get the sample size number.

3.

The adequate sample size is nothing but sufficient sample size.

a. By calculating the starting sample size and ending sample size if a study we can estimate the loss of patients. If there is adequate sample sample size then there is low risk mortality. Minute errors inthe study can also be easily identified. By minising the errors we can decreease the mortality rate.

B . The sufficient sample size is calculated by measuring all the requirements of the study. The study sample shouls meet all the requiements.

C. To determine the specific effectof the treatment a suitable study sample is majorly required. Some studies may require larger sample and some studies may require smaller one. If there is suitable sample size the researcher may analyze the minute side effects and errors in the treatment process and minmize them. If the sample size do not r ach the requiremnts then the there is chance of treatment failure.

D. Develop hypothesis before starting the experiment. Perform alot of background work on the study. Select the criteria of patient population. Collect data and review resulta for every interval. study findings should meet the aim and objective of the study.