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dev_con_6:15:16_cadd_mls [2016/06/16 12:25]
maia_frieser Created page with "'''CADD Discussion 6/15/2016:''' a. Summarized subject counts from CTS and LTS twins for the SAM and SAM supplemental questions. b. Discussed using alcohol and tobacco pheno..."
dev_con_6:15:16_cadd_mls [2016/06/16 13:28] (current)
stephanie_zellers
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 a. Summarized subject counts from CTS and LTS twins for the SAM and SAM supplemental questions.  a. Summarized subject counts from CTS and LTS twins for the SAM and SAM supplemental questions. 
 +
 b. Discussed using alcohol and tobacco phenotypes to get longitudinal information about frequency and quantity b. Discussed using alcohol and tobacco phenotypes to get longitudinal information about frequency and quantity
 +
 c. One problem: lack of consistent questions across 3 waves of data. c. One problem: lack of consistent questions across 3 waves of data.
  
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 - SAM V3: Total # of drinks in a typical week in last year + # drinking weeks in last year - SAM V3: Total # of drinks in a typical week in last year + # drinking weeks in last year
  
-- MTF v1/v2: # drinking occasions/week, # drinks/occasion+- MTF V1/V2: # drinking occasions/week, # drinks/occasion
  
 - SAM supplement V1-3: typical pattern of drinking + days drinking in last 180 days - SAM supplement V1-3: typical pattern of drinking + days drinking in last 180 days
  
 c. Including binge drinking measures from SAM and MTF c. Including binge drinking measures from SAM and MTF
-{{file_example.jpg}}+ 
 +Slides available: [[[https://ibg.colorado.edu/mediawiki/images/c/c8/CADD_6.16.pdf|CADD 6/15/2016]]] 
 + 
 +**MLS Discussion 6/15/2016:** 
 + 
 +1) summarized participant recruitment, participant ID numbers, assessment  
 +schedule, and sample descriptives.  
 + 
 +2) summarized potential variables of interest: variable labels, computation to create composites if available, variable coding 
 + 
 +3) data visualization: 5 number summaries and histograms for selected ages. 
 + 
 +4) discussed issues with missing data, mismatched coding in documentation and data, missing variables of interest 
 + 
 +Future plans 
 + 
 +1) fully examine documentation including MLS data orientation, pedigree, measures, and codebooks 
 + 
 +2) acquire additional data to include more variables of interest 
 + 
 +3) try to identify why some data is missing- skip outs or missing in T wave years? 
 + 
 +4) find data on birth year and recruitment group 
 + 
 +5) separate phenotypes by gender 
 + 
 +6) confirm rescoring structure for variables that do not match codebook 
 + 
 +Slides: [[[https://ibg.colorado.edu/mediawiki/images/d/d5/DevCon_6-15-16.pdf|MLS 6/15/16]]]
  
dev_con_6/15/16_cadd_mls.1466101523.txt.gz · Last modified: 2016/06/16 12:25 by maia_frieser