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Using and Teaching Stata in Emergency Medicine Research Rotation Muhammad Waseem, MD Research Director Emergency Medicine Lincoln Medical & Mental Health.

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Presentation on theme: "Using and Teaching Stata in Emergency Medicine Research Rotation Muhammad Waseem, MD Research Director Emergency Medicine Lincoln Medical & Mental Health."— Presentation transcript:

1 Using and Teaching Stata in Emergency Medicine Research Rotation Muhammad Waseem, MD Research Director Emergency Medicine Lincoln Medical & Mental Health Center Bronx, New York

2 Disclosure Financial disclosures: None

3 Background Participation in scholarly activities is a requirement of an Emergency Medicine (EM) Residency Curriculum A research project is necessary for graduation of EM residents

4 Background In order to fulfill this requirement EM residents have a mandatory research rotation

5 Background ACGME fully accredited 3 year EM Residency Training Program 33 EM residents (11 / year)

6 EM Research Rotation Formulating a research question Basic research designs Protocol writing and submission to IRB Basic statistical concepts Data collection/entry and analysis

7 Background First step in data analysis is to organize the raw data into a format which can be used by Stata Stata is a general purpose statistical package –Physicians versus Programmers

8 Background We believe that the research understanding of EM residents will be enhanced if they are provided with the basic knowledge of a statistical program prior to data collection and data entry The purpose of this training is to equip EM residents with the necessary knowledge and understanding that will help to improve data recording

9 Objective Does providing basic knowledge of a Statistical program (such as Stata) improve the accuracy of data recording and data entry?

10 Methods Design: Observational Setting: Emergency Department of an Urban Teaching Hospital Participants: EM Residents

11 Methods Research Elective –Two blocks of 14 days –1-2 per month (1:1 learning)

12 Methods EM Stata Manual describing basic operation of Stata created with version 10

13 Methods How does EM Stata manual differ from Stata help?

14 Methods How does EM Stata manual differ from Stata help? This manual was developed keeping in mind the needs of in-training EM Residents –First time users EM residents may have some basic knowledge of statistics but little or no knowledge of Stata –Emphasis on data entry and data import

15 Methods Teaches EM residents the essential skills for successful data entry and data import to Stata Purpose is to reduce the number of incorrect entries and make the data set usable to Stata Hands-on experience using Stata

16 Methods Strengths –Tailored to the needs of a specific audience (EM residents) –Discuss only simple and basic operation of Stata

17 Methods Weaknesses –Tailored to the needs of a specific rotation (EM residents research elective) –Does not teach residents detailed statistical analysis –Does not discuss programming

18 Methods Keep it simple We utilize pull-down menus (rather than commands) –No discussion on commands

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20 Methods Getting started Stata screen 4 Windows, 8 Tabs

21 Methods 4 Windows –Review –Variables –Results –Command

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23 Methods 8 Tabs File, Edit, Data, Graphics, Statistics, User, Window, and Help

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25 Methods Basic commands with pull-down menus Describe and summarize data Tables of frequencies Tables of mean Data input and output Data Import Saving files

26 Methods Describe data Data editor Data browser

27 Data Sheets Prior to Introducing Stata

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30 Data Sheets After Introducing Stata

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34 Results Teaching basics of a statistical program (such as Stata) improves the accuracy of data recording and data entry

35 Conclusions Basic operation of Stata can be learned quickly by EM residents Teaching Stata to the EM residents may expand their research related knowledge Providing introduction of Stata prior to data entry improves accuracy of data recording and facilitates data analysis

36 Limitations Small sample Single center study Observational study – not standardized

37 Implications Little effort before data entry can save significant time in data cleaning Teaching statistical program during research rotation makes it more practical and interactive


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