513 lines
19 KiB
Plaintext
513 lines
19 KiB
Plaintext
================================================================================
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EOHI2 DATA PROCESSING PIPELINE - VARIABLE CREATION DOCUMENTATION
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================================================================================
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This README documents the complete data processing pipeline for eohi2.csv.
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All processing scripts should be run in the order listed below.
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Source File: eohi2.csv
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Processing Scripts: dataP 01 through dataP 07
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================================================================================
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SCRIPT 01: dataP 01 - recode and combine past & future vars.r
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================================================================================
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PURPOSE:
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Combines responses from two survey versions (01 and 02) and recodes Likert
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scale text responses to numeric values for past and future time periods.
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VARIABLES CREATED: 60 total (15 items × 4 time periods)
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SOURCE COLUMNS:
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- Set A: 01past5PrefItem_1 through 01fut10ValItem_5 (60 columns)
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- Set B: 02past5PrefItem_1 through 02fut10ValItem_5 (60 columns)
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TARGET VARIABLES:
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Past 5 Years (15 variables):
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- past_5_pref_read, past_5_pref_music, past_5_pref_TV, past_5_pref_nap,
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past_5_pref_travel
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- past_5_pers_extravert, past_5_pers_critical, past_5_pers_dependable,
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past_5_pers_anxious, past_5_pers_complex
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- past_5_val_obey, past_5_val_trad, past_5_val_opinion,
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past_5_val_performance, past_5_val_justice
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Past 10 Years (15 variables):
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- past_10_pref_read, past_10_pref_music, past_10_pref_TV, past_10_pref_nap,
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past_10_pref_travel
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- past_10_pers_extravert, past_10_pers_critical, past_10_pers_dependable,
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past_10_pers_anxious, past_10_pers_complex
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- past_10_val_obey, past_10_val_trad, past_10_val_opinion,
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past_10_val_performance, past_10_val_justice
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Future 5 Years (15 variables):
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- fut_5_pref_read, fut_5_pref_music, fut_5_pref_TV, fut_5_pref_nap,
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fut_5_pref_travel
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- fut_5_pers_extravert, fut_5_pers_critical, fut_5_pers_dependable,
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fut_5_pers_anxious, fut_5_pers_complex
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- fut_5_val_obey, fut_5_val_trad, fut_5_val_opinion,
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fut_5_val_performance, fut_5_val_justice
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Future 10 Years (15 variables):
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- fut_10_pref_read, fut_10_pref_music, fut_10_pref_TV, fut_10_pref_nap,
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fut_10_pref_travel
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- fut_10_pers_extravert, fut_10_pers_critical, fut_10_pers_dependable,
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fut_10_pers_anxious, fut_10_pers_complex
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- fut_10_val_obey, fut_10_val_trad, fut_10_val_opinion,
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fut_10_val_performance, fut_10_val_justice
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TRANSFORMATION LOGIC:
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Step 1: Combine responses from Set A (01) and Set B (02)
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- If Set A has a value, use Set A
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- If Set A is empty, use Set B
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Step 2: Recode text responses to numeric values:
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"Strongly Disagree" → -3
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"Disagree" → -2
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"Somewhat Disagree" → -1
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"Neither Agree nor Disagree" → 0
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"Somewhat Agree" → 1
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"Agree" → 2
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"Strongly Agree" → 3
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Empty/Missing → NA
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ITEM DOMAINS:
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- Preferences (pref): Reading, Music, TV, Nap, Travel
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- Personality (pers): Extravert, Critical, Dependable, Anxious, Complex
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- Values (val): Obey, Tradition, Opinion, Performance, Justice
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================================================================================
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SCRIPT 02: dataP 02 - recode present VARS.r
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================================================================================
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PURPOSE:
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Recodes present-time Likert scale text responses to numeric values.
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VARIABLES CREATED: 15 total
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SOURCE COLUMNS:
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- prePrefItem_1 through prePrefItem_5 (5 columns)
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- prePersItem_1 through prePersItem_5 (5 columns)
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- preValItem_1 through preValItem_5 (5 columns)
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TARGET VARIABLES:
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Present Time (15 variables):
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- present_pref_read, present_pref_music, present_pref_tv, present_pref_nap,
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present_pref_travel
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- present_pers_extravert, present_pers_critical, present_pers_dependable,
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present_pers_anxious, present_pers_complex
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- present_val_obey, present_val_trad, present_val_opinion,
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present_val_performance, present_val_justice
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TRANSFORMATION LOGIC:
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Recode text responses to numeric values:
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"Strongly Disagree" → -3
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"Disagree" → -2
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"Somewhat Disagree" → -1
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"Neither Agree nor Disagree" → 0
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"Somewhat Agree" → 1
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"Agree" → 2
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"Strongly Agree" → 3
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Empty/Missing → NA
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SPECIAL NOTE:
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Present time uses "present_pref_tv" (lowercase) while past/future use
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"past_5_pref_TV" (uppercase). This is intentional and preserved from the
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original data structure.
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================================================================================
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SCRIPT 03: dataP 03 - recode DGEN vars.r
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================================================================================
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PURPOSE:
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Combines DGEN (domain general) responses from two survey versions (01 and 02).
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These are single-item measures for each domain/time combination.
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NO RECODING - just copies numeric values as-is.
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VARIABLES CREATED: 12 total (3 domains × 4 time periods)
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SOURCE COLUMNS:
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- Set A: 01past5PrefDGEN_1, 01past5PersDGEN_1, 01past5ValDGEN_1, etc.
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- Set B: 02past5PrefDGEN_1, 02past5PersDGEN_1, 02past5ValDGEN_1, etc.
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TARGET VARIABLES:
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- DGEN_past_5_Pref, DGEN_past_5_Pers, DGEN_past_5_Val
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- DGEN_past_10_Pref, DGEN_past_10_Pers, DGEN_past_10_Val
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- DGEN_fut_5_Pref, DGEN_fut_5_Pers, DGEN_fut_5_Val
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- DGEN_fut_10_Pref, DGEN_fut_10_Pers, DGEN_fut_10_Val
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TRANSFORMATION LOGIC:
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- If Set A (01) has a value, use Set A
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- If Set A is empty, use Set B (02)
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- NO RECODING: Values are copied directly as numeric
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SPECIAL NOTES:
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- Future columns in raw data use "_8" suffix for Pref/Pers items
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- Future Val columns use "ValuesDGEN" spelling in Set A, "ValDGEN" in Set B
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================================================================================
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SCRIPT 04: dataP 04 - DGEN means.r
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================================================================================
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PURPOSE:
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Calculates mean DGEN scores by averaging the three domain scores (Preferences,
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Personality, Values) for each time period.
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VARIABLES CREATED: 4 total (1 per time period)
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SOURCE COLUMNS:
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- DGEN_past_5_Pref, DGEN_past_5_Pers, DGEN_past_5_Val
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- DGEN_past_10_Pref, DGEN_past_10_Pers, DGEN_past_10_Val
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- DGEN_fut_5_Pref, DGEN_fut_5_Pers, DGEN_fut_5_Val
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- DGEN_fut_10_Pref, DGEN_fut_10_Pers, DGEN_fut_10_Val
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TARGET VARIABLES:
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- DGEN_past_5_mean
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- DGEN_past_10_mean
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- DGEN_fut_5_mean
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- DGEN_fut_10_mean
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TRANSFORMATION LOGIC:
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Each mean = (Pref + Pers + Val) / 3
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- NA values are excluded from calculation (na.rm = TRUE)
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================================================================================
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SCRIPT 05: dataP 05 - recode scales VARS.r
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================================================================================
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PURPOSE:
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Processes two cognitive scales:
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1. AOT (Actively Open-minded Thinking): 8-item scale with reverse coding
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2. CRT (Cognitive Reflection Test): 3-item test with correct/intuitive scoring
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VARIABLES CREATED: 3 total
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SOURCE COLUMNS:
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AOT Scale:
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- aot_1, aot_2, aot_3, aot_4, aot_5, aot_6, aot_7, aot_8
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CRT Test:
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- crt_1, crt_2, crt_3
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TARGET VARIABLES:
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- aot_total (mean of 8 items with reverse coding)
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- crt_correct (proportion of correct answers)
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- crt_int (proportion of intuitive/incorrect answers)
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TRANSFORMATION LOGIC:
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AOT Scale (aot_total):
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1. Items 4, 5, 6, 7 are reverse coded by multiplying by -1
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2. Calculate mean of all 8 items (with reverse coding applied)
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3. Original source values are NOT modified in the dataframe
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4. NA values excluded from calculation (na.rm = TRUE)
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CRT Correct (crt_correct):
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Correct answers:
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- crt_1: "5 cents"
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- crt_2: "5 minutes"
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- crt_3: "47 days"
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Calculation: (Number of correct answers) / (Number of non-missing answers)
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CRT Intuitive (crt_int):
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Intuitive (common incorrect) answers:
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- crt_1: "10 cents"
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- crt_2: "100 minutes"
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- crt_3: "24 days"
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Calculation: (Number of intuitive answers) / (Number of non-missing answers)
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SPECIAL NOTES:
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- CRT scoring is case-insensitive and trims whitespace
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- Both CRT scores are proportions (0.00 to 1.00)
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- Empty/missing CRT responses are excluded from denominator
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================================================================================
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SCRIPT 06: dataP 06 - time interval differences.r
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================================================================================
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PURPOSE:
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Calculates absolute differences between time intervals to measure perceived
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change across time periods for all 15 items.
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VARIABLES CREATED: 90 total (6 difference types × 15 items)
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SOURCE COLUMNS:
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- present_pref_read through present_val_justice (15 columns)
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- past_5_pref_read through past_5_val_justice (15 columns)
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- past_10_pref_read through past_10_val_justice (15 columns)
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- fut_5_pref_read through fut_5_val_justice (15 columns)
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- fut_10_pref_read through fut_10_val_justice (15 columns)
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TARGET VARIABLES (by difference type):
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NPast_5 (Present vs Past 5 years) - 15 variables:
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Formula: |present - past_5|
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- NPast_5_pref_read, NPast_5_pref_music, NPast_5_pref_TV, NPast_5_pref_nap,
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NPast_5_pref_travel
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- NPast_5_pers_extravert, NPast_5_pers_critical, NPast_5_pers_dependable,
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NPast_5_pers_anxious, NPast_5_pers_complex
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- NPast_5_val_obey, NPast_5_val_trad, NPast_5_val_opinion,
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NPast_5_val_performance, NPast_5_val_justice
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NPast_10 (Present vs Past 10 years) - 15 variables:
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Formula: |present - past_10|
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- NPast_10_pref_read, NPast_10_pref_music, NPast_10_pref_TV,
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NPast_10_pref_nap, NPast_10_pref_travel
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- NPast_10_pers_extravert, NPast_10_pers_critical, NPast_10_pers_dependable,
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NPast_10_pers_anxious, NPast_10_pers_complex
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- NPast_10_val_obey, NPast_10_val_trad, NPast_10_val_opinion,
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NPast_10_val_performance, NPast_10_val_justice
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NFut_5 (Present vs Future 5 years) - 15 variables:
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Formula: |present - fut_5|
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- NFut_5_pref_read, NFut_5_pref_music, NFut_5_pref_TV, NFut_5_pref_nap,
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NFut_5_pref_travel
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- NFut_5_pers_extravert, NFut_5_pers_critical, NFut_5_pers_dependable,
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NFut_5_pers_anxious, NFut_5_pers_complex
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- NFut_5_val_obey, NFut_5_val_trad, NFut_5_val_opinion,
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NFut_5_val_performance, NFut_5_val_justice
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NFut_10 (Present vs Future 10 years) - 15 variables:
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Formula: |present - fut_10|
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- NFut_10_pref_read, NFut_10_pref_music, NFut_10_pref_TV, NFut_10_pref_nap,
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NFut_10_pref_travel
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- NFut_10_pers_extravert, NFut_10_pers_critical, NFut_10_pers_dependable,
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NFut_10_pers_anxious, NFut_10_pers_complex
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- NFut_10_val_obey, NFut_10_val_trad, NFut_10_val_opinion,
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NFut_10_val_performance, NFut_10_val_justice
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5.10past (Past 5 vs Past 10 years) - 15 variables:
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Formula: |past_5 - past_10|
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- 5.10past_pref_read, 5.10past_pref_music, 5.10past_pref_TV,
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5.10past_pref_nap, 5.10past_pref_travel
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- 5.10past_pers_extravert, 5.10past_pers_critical, 5.10past_pers_dependable,
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5.10past_pers_anxious, 5.10past_pers_complex
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- 5.10past_val_obey, 5.10past_val_trad, 5.10past_val_opinion,
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5.10past_val_performance, 5.10past_val_justice
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5.10fut (Future 5 vs Future 10 years) - 15 variables:
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Formula: |fut_5 - fut_10|
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- 5.10fut_pref_read, 5.10fut_pref_music, 5.10fut_pref_TV, 5.10fut_pref_nap,
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5.10fut_pref_travel
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- 5.10fut_pers_extravert, 5.10fut_pers_critical, 5.10fut_pers_dependable,
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5.10fut_pers_anxious, 5.10fut_pers_complex
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- 5.10fut_val_obey, 5.10fut_val_trad, 5.10fut_val_opinion,
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5.10fut_val_performance, 5.10fut_val_justice
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TRANSFORMATION LOGIC:
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All calculations use absolute differences:
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- NPast_5: |present_[item] - past_5_[item]|
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- NPast_10: |present_[item] - past_10_[item]|
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- NFut_5: |present_[item] - fut_5_[item]|
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- NFut_10: |present_[item] - fut_10_[item]|
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- 5.10past: |past_5_[item] - past_10_[item]|
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- 5.10fut: |fut_5_[item] - fut_10_[item]|
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Result: Always positive values representing magnitude of change
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Missing values in either source column result in NA
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SPECIAL NOTES:
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- Present time uses "pref_tv" (lowercase) while past/future use "pref_TV"
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(uppercase), so script handles this naming inconsistency
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- All values are absolute differences (non-negative)
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================================================================================
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SCRIPT 07: dataP 07 - domain means.r
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================================================================================
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PURPOSE:
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Calculates domain-level means by averaging the 5 items within each domain
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(Preferences, Personality, Values) for each of the 6 time interval difference
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types.
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VARIABLES CREATED: 18 total (6 time intervals × 3 domains)
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SOURCE COLUMNS:
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- NPast_5_pref_read through NPast_5_val_justice (15 columns)
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- NPast_10_pref_read through NPast_10_val_justice (15 columns)
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- NFut_5_pref_read through NFut_5_val_justice (15 columns)
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- NFut_10_pref_read through NFut_10_val_justice (15 columns)
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- 5.10past_pref_read through 5.10past_val_justice (15 columns)
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- 5.10fut_pref_read through 5.10fut_val_justice (15 columns)
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Total: 90 difference columns (created in Script 06)
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TARGET VARIABLES:
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NPast_5 Domain Means (3 variables):
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- NPast_5_pref_MEAN (mean of 5 preference items)
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- NPast_5_pers_MEAN (mean of 5 personality items)
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- NPast_5_val_MEAN (mean of 5 values items)
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NPast_10 Domain Means (3 variables):
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- NPast_10_pref_MEAN
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- NPast_10_pers_MEAN
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- NPast_10_val_MEAN
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NFut_5 Domain Means (3 variables):
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- NFut_5_pref_MEAN
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- NFut_5_pers_MEAN
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- NFut_5_val_MEAN
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NFut_10 Domain Means (3 variables):
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- NFut_10_pref_MEAN
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- NFut_10_pers_MEAN
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- NFut_10_val_MEAN
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5.10past Domain Means (3 variables):
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- 5.10past_pref_MEAN
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- 5.10past_pers_MEAN
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- 5.10past_val_MEAN
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5.10fut Domain Means (3 variables):
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- 5.10fut_pref_MEAN
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- 5.10fut_pers_MEAN
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- 5.10fut_val_MEAN
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TRANSFORMATION LOGIC:
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Each domain mean = average of 5 items within that domain
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Example for NPast_5_pref_MEAN:
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= mean(NPast_5_pref_read, NPast_5_pref_music, NPast_5_pref_TV,
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NPast_5_pref_nap, NPast_5_pref_travel)
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Example for NFut_10_pers_MEAN:
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= mean(NFut_10_pers_extravert, NFut_10_pers_critical,
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NFut_10_pers_dependable, NFut_10_pers_anxious,
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NFut_10_pers_complex)
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NA values excluded from calculation (na.rm = TRUE)
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PURPOSE OF DOMAIN MEANS:
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- Provides higher-level summary of perceived change by domain
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- Reduces item-level noise by aggregating across related items
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- Enables domain-level comparisons across time intervals
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- Parallel to Script 04 (DGEN means) but for difference scores instead of
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raw DGEN ratings
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SPECIAL NOTES:
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- This script depends on Script 06 being run first
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- Creates domain-level aggregates of absolute difference scores
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- All means are averages of non-negative values (absolute differences)
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================================================================================
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SUMMARY OF ALL CREATED VARIABLES
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================================================================================
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Total Variables Created: 202
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By Script:
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- Script 01: 60 variables (past/future recoded items)
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- Script 02: 15 variables (present recoded items)
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- Script 03: 12 variables (DGEN domain scores)
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- Script 04: 4 variables (DGEN means)
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- Script 05: 3 variables (AOT & CRT scales)
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- Script 06: 90 variables (time interval differences)
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- Script 07: 18 variables (domain means for differences)
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By Category:
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- Time Period Items (75 total):
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* Present: 15 items
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* Past 5: 15 items
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* Past 10: 15 items
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* Future 5: 15 items
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* Future 10: 15 items
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- DGEN Variables (16 total):
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* Domain scores: 12 (3 domains × 4 time periods)
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* Mean scores: 4 (1 per time period)
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- Cognitive Scales (3 total):
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* AOT total
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* CRT correct
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* CRT intuitive
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- Time Differences (90 total):
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* NPast_5: 15 differences
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* NPast_10: 15 differences
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* NFut_5: 15 differences
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* NFut_10: 15 differences
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* 5.10past: 15 differences
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* 5.10fut: 15 differences
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- Domain Means for Differences (18 total):
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* NPast_5: 3 domain means
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* NPast_10: 3 domain means
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* NFut_5: 3 domain means
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* NFut_10: 3 domain means
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* 5.10past: 3 domain means
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* 5.10fut: 3 domain means
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================================================================================
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DATA PROCESSING NOTES
|
||
================================================================================
|
||
|
||
1. PROCESSING ORDER:
|
||
Scripts MUST be run in numerical order (01 → 07) as later scripts depend
|
||
on variables created by earlier scripts.
|
||
|
||
2. SURVEY VERSION HANDLING:
|
||
- Two survey versions (01 and 02) were used
|
||
- Scripts 01 and 03 combine these versions
|
||
- Preference given to version 01 when both exist
|
||
|
||
3. MISSING DATA:
|
||
- Empty cells and NA values are preserved throughout processing
|
||
- Calculations use na.rm=TRUE to exclude missing values from means
|
||
- Difference calculations result in NA if either source value is missing
|
||
|
||
4. QUALITY ASSURANCE:
|
||
- Each script includes QA checks with random row verification
|
||
- Manual calculation checks confirm proper transformations
|
||
- Column existence checks prevent errors from missing source data
|
||
|
||
5. FILE SAVING:
|
||
- Most scripts save directly to eohi2.csv
|
||
- Scripts 04, 06, and 07 have commented-out write commands for review
|
||
- Each script overwrites existing target columns if present
|
||
|
||
6. SPECIAL NAMING CONVENTIONS:
|
||
- "pref_tv" vs "pref_TV" inconsistency maintained from source data
|
||
- DGEN variables use underscores (DGEN_past_5_Pref)
|
||
- Difference variables use descriptive prefixes (NPast_5_, 5.10past_)
|
||
|
||
|
||
================================================================================
|
||
ITEM REFERENCE GUIDE
|
||
================================================================================
|
||
|
||
15 Core Items (Used across all time periods):
|
||
|
||
PREFERENCES (5 items):
|
||
1. pref_read - Reading preferences
|
||
2. pref_music - Music preferences
|
||
3. pref_TV/tv - TV watching preferences (note case variation)
|
||
4. pref_nap - Napping preferences
|
||
5. pref_travel - Travel preferences
|
||
|
||
PERSONALITY (5 items):
|
||
6. pers_extravert - Extraverted personality
|
||
7. pers_critical - Critical thinking personality
|
||
8. pers_dependable - Dependable personality
|
||
9. pers_anxious - Anxious personality
|
||
10. pers_complex - Complex personality
|
||
|
||
VALUES (5 items):
|
||
11. val_obey - Value of obedience
|
||
12. val_trad - Value of tradition
|
||
13. val_opinion - Value of expressing opinions
|
||
14. val_performance - Value of performance
|
||
15. val_justice - Value of justice
|
||
|
||
|
||
================================================================================
|
||
END OF DOCUMENTATION
|
||
================================================================================
|
||
Last Updated: October 1, 2025
|
||
|