Consumer Satisfaction And Types Of Clinical Agencies (Public ✓ Solved

Consumer Satisfaction, and Type of Clinical Agency (Public

1. Identify the independent variable. Identify the dependent variable(s). AGENCY TYPE (PRIVATE OR PUBLIC). GAF and CONSUMER SATISFACTION.

2. Are there any missing values for any of the variables? If there are, what do you recommend doing to address this issue? OF COURSE! REPLACE MISSING VALUE WITH THE MEAN OF THE ENTIRE SERIES.

3. Were there any outliers in this data set? If outliers are present, what is your recommendation? YES! DELETE THE ENTRY BECAUSE THE VALUE WAS NOT VALID (EXCEEDED THE POSSIBLE VALUE).

4. Check the independent and dependent variables for statistical assumptions violations. If there are violations, what do you recommend? THE GAF VIOLATED THE NORMALITY ASSUMPTION. ONCE THE OFFENDING VALUE IS DELETED, THE NORMALITY ASSUMPTION IS INTACT.

5. Write a sample Results section, discussing your data screening activity. GAF, Consumer Satisfaction, and Type of Clinical Agency (Public or Private) Descriptives Extreme Values GAF Stem-and-Leaf Plot for Agency = Private Frequency Stem & Leaf 1.00 Extremes (=<. . .00 extremes>=76) Stem width: 10 Each leaf: 1 case(s) GAF Stem-and-Leaf Plot for Agency = Public Frequency Stem & Leaf 1.00 Extremes ( =<. . .00 extremes>=69) Stem width: 10 Each leaf: 1 case(s) This study was conducted to assess if there are differences between GAF and consumer satisfaction between public or private clinical agencies. Use the SPSS data file for Module 2 (located in Topic Materials) to answer the following questions:

1. Identify the independent variable. Identify the dependent variable(s).

2. Are there any missing values for any of the variables? If there are, what do you recommend doing to address this issue?

3. Were there any outliers in this data set? If outliers are present, what is your recommendation?

4. Check the independent and dependent variables for statistical assumptions violations. If there are violations, what do you recommend?

5. Write a sample result section, discussing your data screening activity.

Paper For Above Instructions

This paper discusses the analysis of the Global Assessment of Functioning (GAF), consumer satisfaction, and the type of clinical agency (either public or private). This assessment is crucial in understanding the efficacy of mental health services rendered by different types of agencies. The dependent variables in this study are GAF scores and consumer satisfaction levels, while the independent variable is the type of agency (public versus private).

Independent and Dependent Variables

The independent variable in this analysis is the type of clinical agency, categorized as either private or public. The dependent variables are the GAF scores and consumer satisfaction levels. Understanding the relationship between these variables provides insights into how agency type might influence the perceived quality of care and patient outcomes.

Missing Values

Upon examining the data set, it is essential to check for any missing values. If missing values are identified, a common approach to address this issue is to replace these values with the mean of the entire series. This imputation method helps maintain the dataset's overall statistical power without significantly skewing the results.

Outliers

In the analysis of GAF and consumer satisfaction, it is also necessary to investigate potential outliers within the dataset. Identifying outliers allows for a more accurate representation of the data. If outliers are present and deemed not valid (such as exceeding expected GAF values), the recommendation is to delete these entries. This process helps to ensure that the analysis is not adversely affected by anomalous data points.

Statistical Assumptions

Statistical assumptions are critical in ensuring the validity of the results derived from the data. One aspect examined is the normality assumption, which pertains to the distribution of GAF scores. If the normality assumption is violated, as identified in this analysis, it is recommended to delete the offending values to restore normality within the dataset. Once these values are managed, the dataset can then be analyzed accurately.

Results Section

The following is a sample Results section based on the data screening activities performed:

GAF, Consumer Satisfaction, and Type of Clinical Agency (Public or Private)

Statistical analysis was conducted to evaluate variations in GAF scores and consumer satisfaction between public and private clinical agencies. Data preprocessing involved checking for missing values, outliers, and statistical assumptions. The stem-and-leaf plot for GAF scores was generated for both agency types, aiding in visualizing the distribution of data points.

For private agencies, the stem-and-leaf plot revealed several extreme values, whereas the public agencies also presented a few extreme scores. It was determined that specific entries exceeded the expected GAF range and were deemed invalid; these entries were subsequently removed from the dataset. After addressing outliers, the normality assumption was satisfied.

Overall, the analysis indicates that differences exist in GAF scores and consumer satisfaction rates when comparing public and private agencies. These findings underscore the importance of agency type in patient assessments and satisfaction measurements, warranting further exploration into how these differences impact patient outcomes.

Conclusion

In conclusion, understanding the relationship between GAF, consumer satisfaction, and the type of clinical agency is vital for improving mental health services. By meticulously addressing missing values, outliers, and statistical assumptions, the analysis showcases the significance of these factors in evaluating healthcare service quality.

References

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