IHP 525 Milestone Two Table

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Information on data set to include in your description Which variables are you investigating? Survivability-fstat Age of patient Identify each variable as continuous/quantitative or categorical, and list the descriptive statistics that are used to describe that type of variable. Age = Continuous/Quantitative Survivability = Categorical Age will be computed: N Mean Standard Deviation Q1 Q3 IQR Will compute against survivability Compute these descriptive statistics for the variables you are investigating and present them here or in a separate table below. See table below What does each statistic tell you about the data for the given variable? N- the number of observations Mean- the mathematic average of the data Standard deviation- a measure of distribution of data Q1- the first 25% of the data Q3- the last 25% of the data; three quartiles below i 75% of the data IQR- middle or 50% of the data
IHP 525 Milestone Two Table A. Assess the collected data . Use this section to lay out the source, parameters, and any limitations of your data. Specifically, you should: 1. Describe the key features of your data set. This is where you want to say where the data came from—describe the sample and how the data was collected. Next, define each of your variables—what do they measure about the subjects? Then describe the distribution of each of your variables using the descriptive statistics you computed. Be sure to assess how these features affect your analysis. The data set that is the focus of this analysis comes from the publishing of Hosmer, et al., 2008 which utilized the Worcester Heart Attack Study as one of the primary data sources. This data was collected over a 26-year period between 1975 and 2001 by focusing on myocardial infarction (MI) admittances to hospitals in the Worcester, MA area and came from the studying of 100 participants across 8 different variables. The primary focus of this analysis is only on the variables of age and follow-up status (fstat) and survivability of patients recovering from myocardial infarction. This data uses 0=alive and 1=dead when considering patient follow-up status while age is a continuous variable. The information informed that the median age of suffering an acute myocardial infarction was 62.67, with a survival rate of 73.61. The minimum likelihood of survival age was 39 years old and the maximum age of 85 years old. The minimum rate of not surviving MI was 32 years old and the maximum age not to survive at 92 years old. Through the examination of age-related survival characteristics, it canbe determined whether older age increases mortality. 2. Analyze the limitations of the data set you were provided with and how those limitations might affect your findings. Justify your response. One of the limitations is that this is a limited data set of 100 patients over a 13-year period which could limit the accuracy of the data and lead to an under or overestimation of the conclusions. Another limitation is that there are many factors that could have an impact on one's survivability that were not considered such as genetics, comorbidities, and social
indicators of health. Not considering these factors allows for the lack of risk adjustment for these variables mentioned and has a direct impact on a patient's morbidity (Gerstman, 2015). References Gerstman, B. B. (2015). Basic Biostatistics: Statistics for Public Health Practice (2cd ed.). Hosmer, D. W., Lemeshow, S., & May, S. (2008). Applied survival analysis: Regression modeling of time to event data: Second Edition[Data set]. New York, NY: John Wiley &Sons Inc.
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