Number of female Medicare enrollees ages 67-69 (2012) in Alabama
Step-By-Step Individual Assignment #2
Topic- number of female medicare enrolless ages 67-69 (2012) in Alabama.
Dataset- Medicare National Dataset
variables- black and white, overall
Is there racial inequality Between white and black Female Medicare Enrollees Age 67-69 in Alabama - 2012
Start with the cover page (1 page, include name, running head).
Please look at the example: http://www.apastyle.org/manual/related/sample-experiment-paper-1.pdf and
Students are required to post their topic and dataset
Introduce the problem or topic being investigated. Include relevant background information that: indicates why this is an issue or topic worth researching; highlights how others have researched this topic or issue (whether quantitatively or qualitatively), and specifies how others have operationalized this concept and measured this phenomena quantitatively (Maximum one paragraph).
1. Literature Review
There is no need for literature review for this assignment
3. What is the Research Question or Research Hypothesis?
Some points for RQ and Hypothesis
There are basically two kinds of research questions: testable and non-testable. Neither is better than the other, and both have a place in applied research.
Examples of non-testable questions are:
How do managers feel about the reorganization?
What do residents feel are the most important problems facing the community?
Respondents' answers to these questions could be summarized in descriptive tables and the results might be extremely valuable to administrators and planners. Business and social science researchers often ask non-testable research questions. The shortcoming with these types of questions is that they do not provide objective cut-off points for decision-makers.
In order to overcome this problem, researchers often seek to answer one or more testable research questions. Nearly all testable research questions begin with one of the following two phrases:
Is there a significant difference between ...?
Is there a significant relationship between ...?
Is there a significant relationship between the age of managers
and their attitudes towards the reorganization?
A research hypothesis is a testable statement of opinion. It is created from the research question by replacing the words "Is there" with the words "There is," and also replacing the question mark with a period. The hypotheses for the two sample research questions would be:
There is a significant relationship between the age of managers
and their attitudes towards the reorganization.
It is not possible to test a hypothesis directly. Instead, you must turn the hypothesis into a null hypothesis. The null hypothesis is created from the hypothesis by adding the words "no" or "not" to the statement. For example, the null hypotheses for the two examples would be:
There is no significant relationship between the age of managers
and their attitudes towards the reorganization.
There is no significant difference between white and minority residents
with respect to what they feel are the most important problems facing the community.
All statistical testing is done on the null hypothesis...never the hypothesis. The result of a statistical test will enable you to either: 1) reject the null hypothesis, or 2) fail to reject the null hypothesis. Never use the words "accept the null hypothesis."
Discuss the Research Methodology (in general). Describe the variable or variables that are being analyzed. Identify the statistical test you will select to analyze these data and explain why you chose this test. Summarize your statistical alternative hypothesis. This section includes the following sub-sections:
4-1. Describe the Dataset
The primary source of data will be HOPSITAL COMPRE MEDICARE DATA (Add citation). This dataset provides information on hospital characteristics, such as: Number of staffed beds, ownership, system membership, staffing by nurses and non clinical staff, teaching status, percentage of discharge for Medicare and Medicaid patients, and information regarding the availability of specialty and high-tech services, as well as Electronic Medical Record (EMR) use (Describe dataset in 2-3 lines, Google the dataset and find the related website to find more information about the data).
Also describe the sample size; for example, “we are using Medicare data-2013, this data includes 3000 obs. for all of the hospitals in the US.”
4-2. Describe Variables
Next, review the database you selected and select a variable or variables that are a “best-fit.” That is, choose a variable that quantitatively measures the concept or concepts articulated in your research question or hypothesis.
Return to your previously stated Research Question or Hypothesis and evaluate it in light of the variables you have selected. (See the sample Table 1).
Table 1. List of variables used for the analysis
Total Hospital Beds
Total facility beds set up and staffed
at the end of reporting period
Source: AHA, 2013
4-3. Describe the Research Method for Analysis
First, describe the research method as a general (e.g., this is a quantitative method and then explain about this method in about one paragraph. If you have this part in the introduction, you do not need to add here).
Then, explain the statistical method you plan to use for your analysis (Refer to content in week 3 on Biostatistics for information on various statistical methods you can choose from), e.g.:
Hypothesis: AZ hospitals are more likely to have lower readmission rates for PN compared to CA.
Research Method: To determine whether Arizona hospitals are more likely to have lower readmission rate than California, we will use a t-test, to determine whether differences across hospital types are statistically significant (You can change the test depends on your analysis).
4-4. Describe statistical package
Add one paragraph for the statistical package, e.g., Excel or Rstudio.
Add at least one paragraph and explain:
▪ Why you needed to see the distribution of data before any analysis (e.g., check for outliers, finding the best fit test; for example, if the data had not normal distribution, you can’t use the parametric test, etc., so just add 1 or 2 sentences).
▪ Did you eliminate outliers? (Please write 1 or 2 sentence, if applicable).
▪ How many observations do you have in your database and how many for selected variables, report % of missing.
▪ When you are finished with this, go for next steps:
- Present the results of your statistical analysis; include any relevant statistical information (summary tables, including N, mean, std. dev.).
For this part you could have at least 1-2 tables and 1-2 figures (depending on your variables bar-chart, pi-chart, or scatter-plot)
- When you have tables and plots ready, think about your finding and state the statistical conclusion. That is, do the results present evidence in favor or the null hypothesis or evidence that contradicts the null hypothesis?
Conclusion and Discussion
▪ Review your research questions or hypothesis. How has your analysis informed this question or hypothesis? Present your conclusion(s) from the results (presented above) and discuss the meaning of this conclusion(s) in light of the research question or hypothesis presented in your introduction.
▪ At the end of this section, add one or two sentences and discuss the limitations associated with this analysis and any other statements you think are important in understanding the results of this analysis.
List of References
Include a reference page listing the bibliographic information for all sources cited in this report. This information should be consistent with requirements specified in the American Psychological Association (APA) format and style guide.
Number of female Medicare enrollees ages 67-69 (2012) in Alabama
History has it that there is no single time that there has been equality of the health status of the minority populations and the white Americans. Even though there has been a significant improvement in the health of these minority communities, still equality has not been achieved, and there are records of excess morbidity and reduced life expectancy for the blacks and other minority groups such as the African Americans and the Native Americans (Bhave et al. 2015). There has been an awareness among researchers in healthcare, clinicians and even advocates that there is a dire need for improving healthcare outcomes. This proposal is more effective especially for the underserved population in the American healthcare system which comprises of the African Americans, Asian Americans, Native Americans and the Latinos (Betancourt et al. 2014). The general statistics show that there is are significant overall visits to medical facilities in Alabama. Records provided by the Medicare National Data by the county in 2012 showcased that there is a low enrollment in Alabama among the black and white ages between 67-69 (National Center for Health Statistics; the US, 2016). The result is a proof of racial inequality in health care revealing that the blacks have fewer visits to medical facilities as compared to the white. All the data are organized in Excel statistical package.
Is there racial inequality between white and black Female Medicare Enrollees Age 67-69 in Alabama - 2012
The study will employ the use of surveillance, epidemiology and 2012 Medicare database in the course of identifying whether there is a racial inequality between the white and black female Medicare enrollees between the ages 67-69 in Alabama. Variables for evaluation within this particular study are the differences between the independent variables which are white and black female patients aged 67-69 in Alabama against the dependent variable which is the overall number of female patients who enroll in Medicare in Alabama. The study will be carried out both qualitatively and quantitatively. Qualitative data will be drawn from other scholarly research and interviews conducted among healthcare professionals and residents of Alabama, both blacks, and whites. The qualitative data are used as a foundation for a quantitative study to be accomplished. On the other hand, a quantitative approach will be used in this study. By quantitative approach, the researchers denote to methods of randomized experiments and sample surveys. These methods allow for the quantifying of results in numbers, therefore, providing a method for measurement that paves for a more exact form (Holloway & Galvin 2016). The researcher will use hierarchical logistic regression to assess if there was racial inequality among the black and white females aged 67-69. Hierarchical logistic regression is the best statistical test as it has the capability of examining the rate of enrollment in medical facilities as provided by the data.
The study will employ the use of Excel in entry and manipulation of data. Numerous studies have ascertained that excel is a convenient tool in the course of data entry. The Excel statistical package is the best tool for this particular study as it has the capability of manipulating rows and columns that are essential in statistical analysis. Data for all the variables; black and white, overall are going to be arranged in Excel after which statistical analysis will be carried out using SPSS statistical package.
The analysis will be best done after data distribution to evaluate whether data distribution was a success or not. From the hierarchical logistic regression, the researcher will then come up with the results regarding the findings as based on the research questions. Outliers that will be eliminated from these study are female aged either below 67 or above 69 and those not living Alabama. There are ten observations in the medical database, and all of them are used for the selected variables.
The analysis will perfectly inform the research question. With the use of hierarchical logistic regression, the research will be in a position of testing the data gathered. The only limitation with this analysis is that the 2012 data used might not be a direct reflection of the actual case in Alabama since there have been some changes in the medical sector since then.
Betancourt, J. R., Green, A. R., Carrillo, J. E., & Owusu Ananeh-Firempong, I. I. (2016). Defining cultural competence: a practical framework for addressing racial/ethnic disparities in health and health care. Public health reports.
Bhave, P. D., Lu, X., Girotra, S., Kamel, H., & Sarrazin, M. S. V. (2015). Race-and sex-related differences in care for patients newly diagnosed with atrial fibrillation. Heart Rhythm, 12(7), 1406-1412.
National Center for Health Statistics (US. (2016). Health, United States, 2015: with special feature on racial and ethnic health disparities.
Holloway, I., & Galvin, K. (2016). Qualitative and Quantitative research in nursing and healthcare. John Wiley & Sons.
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