Select one of the more common statistical tests used in nursing research. State which statistic you selected. What level of measurement is required for using your chosen statistical test? Provide an example of how your selected statistical test could be used in a nursing research study.
Chi-square test
Statistical tests are essential tools in nursing research that help analyze and interpret data, enabling researchers to draw meaningful conclusions from their studies. One of the more common statistical tests used in nursing research is the Chi-square test. The Chi-square test is a non-parametric test that assesses the association between categorical variables and is applicable when the level of measurement for the variables is nominal or ordinal.
The Chi-square test requires categorical variables, which are characterized by nominal or ordinal levels of measurement. Nominal variables have categories without any inherent order, such as gender (male/female) or blood type (A/B/AB/O). Ordinal variables, on the other hand, have categories with a specific order but lack equal intervals between them, such as pain level (mild/moderate/severe) or educational level (high school/college/postgraduate).
Research Question: Does a patient’s adherence to a prescribed medication regimen differ based on their age group?
In this hypothetical nursing research study, researchers aim to determine if age group influences a patient’s adherence to a prescribed medication regimen. The variables involved are “Age Group” (categorical with nominal level of measurement) and “Medication Adherence” (categorical with ordinal level of measurement).
Data Collection: The researchers recruit a sample of 300 patients from different age groups (18-30, 31-50, and 51-70 years) who are on the same medication regimen for a chronic condition. They categorize medication adherence as “Poor,” “Fair,” and “Good,” based on the percentage of prescribed doses taken by the patient over a specific time frame.
Data Analysis: The researchers use the Chi-square test to determine if there is a significant association between age group and medication adherence. They conduct the test using a contingency table that cross-tabulates the two variables: Age Group (rows) and Medication Adherence (columns).
Results: The Chi-square test outputs a p-value, which represents the probability of obtaining the observed results if there were no real association between age group and medication adherence. If the p-value is less than the predetermined significance level (e.g., 0.05), the researchers can conclude that age group is significantly associated with medication adherence.
The Chi-square test is a valuable statistical tool in nursing research, particularly when examining the association between categorical variables with nominal or ordinal levels of measurement. In the example provided, the Chi-square test allows researchers to investigate whether a patient’s age group affects their adherence to a prescribed medication regimen. By utilizing this statistical test, nursing researchers can gain valuable insights to inform clinical practice, patient care, and intervention strategies, ultimately enhancing patient outcomes and promoting evidence-based nursing practice.
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