Meta Data Standards for Managing and Archiving Longitudinal Data: Achieving Best Practice Melanie Spallek*, Michele Haynes* & Mark Western* presented by Steven McEachern *The Institute for Social Science Research (ISSR)

Brisbane Institute of Social Science Research at the University of Queensland ASSDA – Queensland node

WHY Cross-sectional and longitudinal data structure is different Current meta data standards not sufficient Great need for international standard in best practice for archiving longitudinal data

Overview Cross-sectional studies versus longitudinal studies >different types of longitudinal studies Major longitudinal studies archived with ASSDA Challenges with documenting longitudinal studies Compare meta data standards internationally Future plans at ASSDA

Cross- sectional Multiple variables observed at a single point in time One- dimensional Longitudinal Repeated observations over time Two or more dimensional Change over time, cause- effect, shifting attitudes

Different types of longitudinal studies Repeated cross-sectional studies > new sample at different points in time > represents snapshot of population at each time point > aspect of individual’s change not available Cohort studies > group of individuals at a similar state in the life course, studied over time > problems with drop-outs Household panels > Household as a study unit > Number of individuals can vary (move in, move out)

Major longitudinal studies archived with ASSDA Negotiating the Life Course (NLC) > 1500 participants at wave 1 in 1996 > five waves archived so far Australian Longitudinal Study on Women's Health (ALSWH) > three cohorts (younger, mid-aged, older) > 40,000 participants at wave 1 in 1996 > four waves archived for the younger and older cohorts and five for the mid-aged cohort

Australian Longitudinal Survey of Ageing (ALSA) > 2,087 participants at wave 1 in 1992 > seven waves archived so far Longitudinal Surveys of Australian Youth (LSAY) > 13,613 participants at wave one in 1995 > all four waves have been archived Longitudinal Survey of Immigrants to Australia (LSIA) >Phase 1 (three waves) and Phase 2 (two waves) have been archived Professor Mary Luszcz with the oldest ALSA participant who is 108 years old.

DDI2 is used for describing cross-sec and longitudinal data coverage of DDI2 is focused on single studies, single data files, simple surveys and aggregated data files metadata requirements for longitudinal studies differ from that of cross-sectional studies and also across types of longitudinal studies DDI3.1 supports the description of longitudinal data, but few archives have facilitated DDI3.1 yet Meta data standards used at ASSDA

Challenges Combining Data on Same Individuals from Repeated Surveys –How do longitudinal studies name comparable variables at different surveys? –What tools are in place to easily identify variables and their comparability? –What makes a variable incomparable?

survey variable name valuesquestion variable relates to 1m1q30bn/a non existent 2m2q30b1,2,3,4,5,6,. Over the last 12 months, how stressed have you felt about the following areas of your life: Health of other family members. 1 n/a, 2 not at all stressed, 3 somewhat stressed, 4 moderately stressed, 5 very stressed, 6 extremely stressed 3m3q30b0,1,. Some women have experienced difficulties in becoming pregnant. Have you ever had any of the following problems with fertility: You were diagnosed as infertile by a doctor? 1 yes, 0 no 4m4q30bn/a non existent 5m5q30b1,2,3,4,5,6,. Thinking about your own health care, how would you rate the following: Access to hospital if you need it. 1 excellent, 2 very good, 3 good, 4 fair, 5 poor, 6 don't know

AgreeDisagree Strongly Agree Strongly Disagree Survey 1: Marriage improves your health Survey 2: Marriage improves your health Incomparability

Challenges Combining data on same individuals from repeated surveys –How do longitudinal studies name comparable variables at different surveys? –What tools are in place to easily identify variables and their comparability? –What makes a variable incomparable? Updating longitudinal surveys

Updating Longitudinal Surveys Additional logic check within a study participant between surveys across time S1 S2 S3 S1 Osteoporosis S2 Osteoporosis S3 Osteoporosis

Comparisons among International Archives UK Data Archive’s Survey Question Bank CentERdata uses some DDI Other archives have not been found to address issues relating meta data for longitudinal data archiving

Future Plans at ASSDA Website for longitudinal data archiving Provide guidelines for data dictionary and variable map development Require data dictionary and variable map with deposit of longitudinal data

Website/ Contact Australian Social Science Data Archive 18 Balmain Crescent The Australian National University ACTON ACT Website: Phone: Fax: