Independent and dependent variables.

Post your research question and describe the independent and dependent variables. Then, identify the level of measurement of both your independent and dependent variables. Provide a brief rationale for your classification of each variable. Be specific. Explain considerations of analyzing data related to each variable based on its level of measurement. Be sure to include any advantages or challenges that you might encounter in your statistical analysis of each variable and explain why.

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Sample Answer

 

 

Research Question: Does implementing a nurse-led medication education program improve medication adherence among elderly patients with heart failure?

Variables:

  • Independent Variable: Nurse-led medication education program (categorical)

    • This variable has two categories: participation (exposed to the program) or non-participation (not exposed to the program).
  • Dependent Variable: Medication adherence (ordinal)

    • Medication adherence can be measured on a scale, such as:
      • High adherence (80% or more medication doses taken as prescribed)
      • Medium adherence (50-79% of doses taken)

Full Answer Section

 

 

 

Level of Measurement Rationale:

  • Independent Variable (Categorical): The program participation is either yes (participated) or no (not participated). It doesn’t involve any ranking or order, making it categorical.
  • Dependent Variable (Ordinal): Medication adherence can be measured on a scale with ordered categories (high, medium, low), but the intervals between these categories may not be equal. For example, the difference between high and medium adherence might be more significant than the difference between medium and low adherence.

Data Analysis Considerations:

  • Independent Variable (Categorical): Since the independent variable is categorical, statistical tests appropriate for comparing groups, such as Chi-square tests or t-tests (depending on additional factors), would be used to assess if there’s a statistically significant difference in medication adherence between the program participation groups.
  • Dependent Variable (Ordinal): The ordinal level of the dependent variable presents some challenges. Ideally, interval or ratio data (equal intervals) would be preferable for parametric tests like ANOVA. However, with ordinal data, non-parametric tests like the Mann-Whitney U test or Kruskal-Wallis test can be used to compare medication adherence across the program participation groups.

Advantages and Challenges:

  • Advantages: Ordinal data allows us to analyze the order or direction of the relationship between the variables (i.e., higher program participation might be associated with higher medication adherence).
  • Challenges: Ordinal data may not capture the true magnitude of the difference between adherence levels. Statistical tests for ordinal data might be less powerful than those for interval or ratio data.

In conclusion:

This study design allows us to investigate the association between a nurse-led medication education program and medication adherence in elderly patients with heart failure. While the ordinal level of the dependent variable presents some limitations, we can still employ appropriate non-parametric tests to analyze the data and draw meaningful conclusions about the program’s effectiveness.

 

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