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Introduction to Stata using the Northern Ireland Household Panel Survey (NIHPS)

Introduction to Stata using the Northern Ireland Household Panel Survey (NIHPS). Katrina Lloyd (QUB) Patricia McKee (UU). Format. 9:15 Intro to NIHPS 9:30 Intro to Stata 10:30 – 11:00 Coffee break 11:00 Stata files – log / do Advantages of Stata 12:30 Questions / examples. NIHPS.

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Introduction to Stata using the Northern Ireland Household Panel Survey (NIHPS)

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  1. Introduction to Statausing the Northern Ireland Household Panel Survey (NIHPS) Katrina Lloyd (QUB) Patricia McKee (UU)

  2. Format • 9:15 Intro to NIHPS • 9:30 Intro to Stata • 10:30 – 11:00 Coffee break • 11:00 Stata files – log / do Advantages of Stata • 12:30 Questions / examples

  3. NIHPS • NIHPS began in 2001 and is an extension of the BHPS (1991) • ISER at Essex University has overall responsibility for survey • NISRA carries out fieldwork in NI • 6 waves of NIHPS data available from UK Data Archive (2001-2006)

  4. NIHPS • NIHPS follows representative sample of individuals • Household-based interviewing: • All adults aged 16+ • From Wave 4 all children aged 11-15 (Youth Panel) • Unique value is that NIHPS measures change at the individual level

  5. NIHPS • Achieved sample (full interviews all years) • Wave 1 - 3,458 individuals in 1,978 households • Wave 2 - 2,692 individuals • Wave 3 - 2,414 individuals • BY Wave 6 - 2,151 individuals • Attrition

  6. Content of the NIHPS • NIHPS has 3 components: • Core component asked every year • Includes health, housing, finances • Rotating core component – every 3 years • Includes wealth, assets and debt, parenting • Variable component – once in the panel • Includes race, place of birth, age left school

  7. NIHPS datasets • Cross-sectional files for each wave • Longitudinal files for individuals • Files linked by common variables • PID (unique Personal Identification Number) • wHID (Household ID – changes year on year) • wPNO (person number – changes year on year) • w refers to the wave id k,l,m,n,o,p - years 2001-2006 respectively

  8. NIHPS Record Type Record Description wHHSAMP - household-level data for issued households wHHRESP - household-level data for responding households wINDSAMP - individual-level data for issued households wINDALL - enumerated individuals' data (including children and non- respondents)

  9. NIHPS Record Type Record Description wINDRESP - individual-level data for respondents wEGOALT - relationship of each individual in a household wINCOME - income and payment data wJOBHIST - information from the employment history

  10. NIHPS additional files wMARRIAG - one record for each reported legal marriage wCOHABIT - one record for each cohabitation spell outside marriage wCHILDAD - information about adopted and/or step- children wCHILDNT - information about natural children wCHILD - information on children and parenting styles wYOUTH - responses to the Young persons questionnaire wLIFEMST - information about employment status spells

  11. NIHPS additional files For ALL Waves XWAVEID - information for matching individuals between waves XWLSTEN - information on the latest known sample status of individuals XWAVEDAT - central source of data on individuals which is fixed and only measured once in the panel e.g. race

  12. Files using today: wINDALL

  13. Stata windows Previous commands Results Variables Commands

  14. Edit Preferences Click on Edit tab Come down to preferences Select general preferences

  15. LOG files – record your session • Start • Either click icon or select File > Log > Begin • Types • .smcl = Stata formatted • .log = a text file or ASCII file  • Choices • View existing file • Append new to old • Overwrite with new • Closure • When you exit • Choose to suspend / resume

  16. Log file Choose folder LOG file Give filename Choose type LOG Note : if a log file is on the name appears below results and above commands

  17. DO files • Text file containing commands rather than typing commands at the keyboard • Contents of review window (previous commands can be saved into a do file • Do files may call other do-files which call other do-files nested 64 deep orin a master.do up to 1,000 do files can be called one after the other

  18. Do file Note: comment Select commands to run and click icon

  19. Built-in Variables • _pi contains the value π to machine precision • _n contains the number of the current obs. • Eg age 23 34 45 56 _n 1 2 3 4 • _N contains the total number of obs. • Eg age 23 34 45 56 _N 4 4 4 4 Note Stata respects case: 3 distinct names myvar Myvar MYVAR

  20. Example of _n and _N use kindall, clear sort khid kpno // sort file hhold and pno within gen totcases = _N // generate total number of obs * For each hhold generate no of people in hhold bysort khid: gen totninhh = _N * For each hhold generate the number within bysort khid: gen nwithinhh = _n list pid khid kpno totninhh nwithinhh in 1/20 tab totninhh nwithinhh ,miss // crosstab include missing

  21. gen totcases = _N // generate total number of obs tab totcases

  22. bysort khid: gen totninhh = _N tab totninhh totninhh Freq. Percent Cum. 1 518 9.98 9.98 2 1,238 23.86 33.85 <- 2 persons 3 915 17.64 51.48 4 1,176 22.67 74.15 <- 4 persons 5 830 16.00 90.15 6 252 4.86 95.01 7 175 3.37 98.38 8 56 1.08 99.46 9 18 0.35 99.81 10 10 0.19 100.00 Total 5,188 100.00

  23. list pid khid kpno totninhh nwithinhh in 1/20 Case pid khid kpno totninhh nwithinhh 1. 118500023 11850027 1 3 1 2. 118500058 11850027 2 3 2 3. 118500074 11850027 3 3 3 4. 118500317 11850043 1 1 1 5. 118501135 11850116 1 1 1

  24. Saved Results summarize produces summary statistics sum kage12  Variable Obs Mean Std. Dev. Min Max kage12 5188 35.46164 22.59792 0 97 Also saves in r( ) 19 scalars like: r(N) – no of obs r(mean) – mean r(sum) – sum of age r(sd) – std deviation r(p1) – 1st percentile r(p95) 95th percentile some are only available with sum kage12, detail To list results stored in r( ) type return list

  25. . sum kage12, detail age at 1.12.2001 Percentiles Smallest 1% 0 0 5% 3 0 10% 6 0 Obs 5188 25% 16 0 Sum of Wgt. 5188 50% 34 Mean 35.46164 Largest Std. Dev. 22.59792 75% 53 92 90% 68 94 Variance 510.6658 95% 75 96 Skewness .2723639 99% 83 97 Kurtosis 2.072386

  26. scalars: r(N) = 5188 r(sum_w) = 5188 r(mean) = 35.46164225134927 r(Var) = 510.66577343513 r(sd) = 22.59791524533026 r(skewness) = .2723638715033958 r(kurtosis) = 2.072386222684342 r(sum) = 183975 r(min) = 0 r(max) = 97 r(p1) = 0 r(p5) = 3 r(p10) = 6 r(p25) = 16 r(p50) = 34 r(p75) = 53 r(p90) = 68 r(p95) = 75 r(p99) = 83 After sum kage12,detail type return list

  27. LOCAL variables eg var referred to as `var’` from key beside 1 and ‘ from key down beside L Programming - loop over items/values • foreachvar in – loops over items • Can be varlist or newlist or numlist • forvaluesx = – loops over consecutive values • loop is executed as long as `x’ is in range

  28. Example * Comment Setup a local variable testvars local testvars " khgr2r khgsex kage12" * Start of loop – note { and ending } * Could also use foreach x in khgr2r khgsex kage12 { foreach x of local testvars { display " the current variable is `x' tab `x' // displays frequencies sum `x' // produces summary statistics ret list // displays all the saved results } // end of loop

  29. Merging data files • Two kinds of merges • One-to-one • Match-merge • Result contained in new var _merge • 1 = obs occurred ONLY in master dataset • 2 = obs occurred ONLY in using dataset • 3 = obs occurred in BOTH master and using datasets

  30. Example of merging Local dirdata “j:\nihps\nihps data\” foreach x in k l m n o p { use “`dirdata’`x'indall”, clear keep pid `x'age12 `x'newhy sort pid save temp`x’,replace } use tempk,clear foreach x in l m n o p { merge pid using temp`x', _merge(mer`x') sort pid }

  31. Command to check number of obs: tab1 *newhy

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