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2018 NM Community Survey Data Entry Training

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Presentation on theme: "2018 NM Community Survey Data Entry Training"— Presentation transcript:

1 2018 NM Community Survey Data Entry Training
March 14 & 15, 2018

2 Data Entry - in General 8 codebooks, one for each module
Core Module: variable names start with CR Tobacco Module: variable names start with TO Mental Health Module: variable names start with MH College Community Module: variable names start with CG Community Module: variable names start with CU Opioid Module: variable names start with OP Gambling Module: variable names start with GA ACEs Module: variable names start with ACE SPSS & Excel data entry templates The Excel template has been pre-programmed with required values for the majority of questions (this should prevent you from entering out of range values). DO NOT CHANGE pre-programmed values in the Excel file to accommodate the survey you are entering. All modules are in the same file. You can delete the modules you don’t use from the templates. Everything is located at: Survey.html

3 Data Entry - Survey administrative questions
Make sure to enter: Site ID/location/Initials/PID (in order to check the original surveys if there are any data entry errors) use consecutive numbers 1-n to enumerate PIDs. Variable English: not in the survey, but in the data entry template; helps us know how many Spanish surveys were collected in a location String variable location Please DO NOT use numeric value for survey venues (e.g., 1,2,) Create a list of abbreviations for survey venues (e.g., Wal- Mart=WM) if that makes it easier but words/letters (strings) are required for this variable and not numbers. Date: not in the survey, you can add it if you need it (for storing surveys by dates).

4 Data Entry – Basic rules
If a question is not answered, leave it blank in the data entry file; do not attempt to answer it for them If age is missing or a respondent indicates that s/he does not live in NM (CR3=888), then remove this survey due to ineligibility of participating in NMCS. Questions with skip patterns: If a respondent answers a question they weren’t supposed to, the syntax will deal with it later. Go ahead and enter whatever response was checked in the survey. For example: if someone over 21 answers questions intended for 18 to 20 year olds only (CR24), please enter the data anyway. If someone answers more than one response when only one response is required, leave it blank or missing.

5 Data Entry –Specific questions
CR10 zip codes: only NM zip codes allowed ( ). If it’s non-NM zip code, leave this question blank (the respondent may not be a NM resident). CR19 (# of drinks per week)/CR21 (binge drinking)/CR22 (DWI): ask for numeric values that require respondents to write down a number. Enter numbers only; Do NOT enter text. For example: CR21 ___times (binge drinking) in past 30 days. Do not enter text, e.g., CR21=many times, leave it blank instead If CR21=20-30 times, enter a midpoint value (i.e., 25) CR42 (what is “A Dose of Rxeality”): only one correct answer required. BUT if there are multiple selections, treat them as missing (i.e., leave all of them blank).

6 Data files Turn in data files (ideally cleaned) by May 15th .
If you have access to SPSS, you should be able to clean the data by running the cleaning SPSS syntax. We will attempt to get everyone’s aggregated data files to them as soon as possible once we receive your file. The data collection will end on April 28th. Assuming everyone has submitted their data to PIRE on time, we will be ready to send back your data files by May 30th, giving you 6 weeks to complete your end of year report documents

7 Questions on Data Entry

8 SPSS syntax Will be available at: Survey.html Clean data-using the cleaning syntax file Create variables-using the variable creation syntax file Run analyses— using the analyses syntax file Keep a master data file (the original data file!) and create a working dataset that only includes eligible respondents for analyses Must be age 18+ and NM residents

9 Questions on Data Analysis

10 Reporting templates and SPSS syntax
Analysis Variable names are provided in the reporting template to facilitate entering results into the reporting template Table numbers are provided in the syntax to identify which syntax is for which table; this will also be in the results when you run the syntax All analyses exclude missing data (this means the valid N is the number you will report in your final reports) Figures: Use Excel to create figures

11 Evaluation report write-up
Use these questions as guide to summarize your findings This is where your evaluator should be very helpful! Remember to talk about the results within the context of the community and the data collection process, etc. Compare males vs. females at the very least (also consider age, race/ethnicity, drinkers vs. non-drinkers, etc.) Include multiple year comparisons if you have previous survey data: e.g., past 30-day alcohol consumption Overall comparison: How is the 2018 prevalence rate compared with the rate from previous years? Up, down, no change? Why? Comparison by sex: How is the 2018 prevalence rate among males compared with the rate from previous years? How about females? Why? Comparison by age groups: How is the 2018 prevalence rate across age groups compared with the rate from previous years? Why? Any trend observed across years? Any explanations? Why?

12 Evaluation report write-up
Your evaluator may be preparing a Powerpoint presentation on your data results. You may submit the slides in lieu of the reporting template but it needs to be comprehensive and it needs to include the interpretation of the results. Compare your sample demographics to what you reported in the data collection protocol you submitted for the community. Are they similar? If not, how do you think your results are influenced by your sample? Estimates too high, too low?

13 For example… In year 2016, 50% of your sample was male and the average age of the sample was 35. In year 2017, 35% of your sample was male and the average age was 45. In year 2018, 25% of your sample was male and the average age was 55. How might this affect the prevalence rate of risky behaviors, particularly related to alcohol? Increase binge drinking prevalence over the 3 years Decrease binge drinking prevalence over the 3 years Binge drinking prevalence stays about the same over the 3 years

14 Questions?


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