• Understand the kinds of research questions that can be answered through longitudinal designs;
  
• Take steps to reduce the threats to internal and external validity inherent in longitudinal designs, particularly the threats that result from decreasing sample size over time;
• Assess the explanatory power, and internal and external validity of longitudinal designs;
• Understand the barriers associated with repeated data collection over time
• Create loongitudinal designs
  

Topic 1: Why should social scientists use more longitudinal studies? OR What do we miss when we do NOT use longitudinal studies?

Learning Guide Longitudinal Designs

Advantages and Disadvantages of Longitudinal Designs Very short, easy to read, good summary

DeVaus, David. (2007) Types of longitudinal designs. Pp. 113-130 in Research Design in Social Research, Sage, Thousand Oaks, CA. e reserve This is a very important reading. DeVaus is really good on longitudinal designs AND pretty easy to read.

Bjarnason, T. & Adalbjarnardottir, S. (2000) Anonymity and confidentiality in school surveys on alcool and cannabis use. Journal of Drug Issues 30(2), 335-344. Maintaining anonymity is a major problem with longitudinal designs. I recommend that you peruse this article enough to understand the issue.

Topic 2: Egads -- longitudinal data analysis!

We are not going to delve into the depths of longitudinal data analysis in this class. Data analysis for longitudinal designs is complex. Whatever you do consult a statistician if you have longitudinal data -- including pre- and post-tests for things like training events.

Start with something easy -- my slide show which is woefully inadequate, but might get the idea across. We will go over this in class. Remember that you need to use these analysis tecniques in any study where there is a "pre and post" measurement of some sort. Longitudinal Designs Slide Show

Now let's try something more sophisticated, but still very basic. It's only 10 minutes long and it gives a GOOD description of the very basics of longitudinal analysis. Analysing Longitudinal Data.

Garcia, T.P. & Marder, K. (2017) Statistical approaches to longitudinal data analysis in neurodegenerative diseases: Huntington's disease as a model. Current Neurology & Neuroscience Reports 17:14 DOI 10.1007/s11910-017-0723-4. This article is only for those with GOOD knowledge of statistical analyses. If you are at the basic stats level, do not read this. Link to this article provided by United States National Library of Medicine This article is FAR superior to the comments about data analysis in my slide show. Garcia & Marder talk about "starter approaches" to data analysis -- and that is what is in my slide show with a focus on the perils of using simple raw scores at two or more points in time. On the contrary, Garcia & Marder have the "real deal" about statistical measurements in longitudinal studies. Please rely on Garcia & Marder -- not my slide show -- if you are a sophisticated user of statistics.

Additional Resources -- Good materials for Sharing Materials on the Canvas discussion board. Please remember that you can earn bonus points for additional shares beyond the two required shares. You have to post at least two times, but I will count up to two more postings for credit (total of 50 points possible)

Aerenhouts, D., Clarys, P. Taeymans, J. & Van Cauwenberg, J. (2015) Estimating body composition in adolescent sprint athletes: Comparison of different methods in a e years longitudinal design. PLoS ONE 10(8), 1-10. DOI: 10.1371/journal.pone.0136788

Amico, K.R. (2009) Percent total attrition: A poor metric for study rigor in hosted intervention designs. American Journal of Public Health 99(9), 1567-1575.

David, M.C., Alati, R., Ware, R.S. & Kinner, S.A. (2013) Attrition in a longitudinal study with hard-to-reach participants was reduced by ongoing contact. Journal of Clinical Epidemiology 66(5), 575-581. 10.1016/j.jclinepi.2012.12.002.

Davies, K., Kingston, A., Robinson, K. et al. (2014) Improving retention of very old participants in longitudinal research: experiences from the Newcastle 85+ study. PLoS ONE 9(10), 1-10. DOI: 10.1371/journal.pone.0108370.

Estrada, M., Woodcock, A. & Wesley Schultz, P. (2014) Tailored panel management: A theory-based approach to building and maintaining participant commitment to a longitudinal study. Evaluation Review 38(1), 3-28. DOI: 10.1177/0193841X14524956.

Heo, M. (2014) Impact of subject attrition on sample size determinations for longitudinal cluster randomized clinical trials. Journal of Bipharmaceutical Statistics 24(3), 507-522. DOI: 10.1080/10543406.2014.888442.

Hubert-Williams, L., Hastings, R., Owen, D.M. et al. (2014) Exposure to life events as a risk factor for psychological problems in adults with intellectual disabilities: A longitudinal design. Journal of Intellectual Disability Research 58(1), 48-60. DOI: 10.1111/jir.12050.

Kent, S., Chen, R., Kumar, A. & Holmes, C. (2010) Individual growth curve modeling of specific risk factors with memory in youth with Type 1 diabetes: An accelerated longitudinal design. Child Neuropsychology 16(2), 169-181. DOI: 10.1080/09297040903264140.

Lacey, R.J., Jordan, K.P., Croft, P.R. (2013) Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status? PLoS ONE 8(12), 1-18. DOI: 10.1371/journal.pone.0083948.

Ledford, J.R., Barton, E.E., Hardyk J.K. et al. 2016) What equivocal data from single case comparison studies reveal about evidence-based practices in early childhood special education. Journal of Early Intervention 38(2), 79-91. DOI: 10.1177/1053815116648000.

Lin, J., Ju, Y., Lee, W. et al. (2011) Examining changes in self-perceived quality of life in children and adolescents with physical disability using a longitudinal design. Disability & Rehabilitation 33(19/20), 1873-1879. DOI: 10.3109/09638288.2011.552664.

Marzell, M., Turrisi, R., Mallett, K. et al. (2014) Combining alcohol and energy drinks: An examination of psychosocial constructs and alcohol outcomes among college studenets using a longitudinal design. Addiction Research & Theory 22(2), 91-97. DOI: 10.3109/16066359.2013.804510.

Pinto-Foltz, M.D., Logsdon, M.C. & Derrick, A. (2011) Engaging adolescent mothers in a longitudinal mental health intervention study: Challenges and lessons learned. Issues in Mental Health Nursing 32(4), 214-219. DOI: 10.3109/01612840.2010.544841.

Roy, A., Bhaumik, D.K., Aryal, S. & Gibbons, R.D. (2007) Sample size determination for hierarchical longitudinal designs with differential attrition rates. Biometrics 63(3), 699-707. DOI: 10.1111/j.1541-0420.2007.00769.x.

Schoeppe, S., Oliver, M., Badland, H., et al. (2014) Recruitment and retention of children in behavioral health risk factor studies: REACH strategies. International JOurnal of Behavioral Medicine 21(5), 794-803. DOI: 10.1007/s12529-013-9347-5.

Thygesen, L.C., Johansen, C., Keiding, N. et al. (2008) Effects of sample attrition in a longitudinal study of the association between alcohol intake and all-cause mortality. Addiction 103(7), 1149-1159. DOI: 10.1111/j.1360-0443.2008.02241.x.

Wu, W., Jia, F., Rhemtulla, M. & Little, T. (2016) Search for efficient complete and planned missing data designs for analysis of change. Behavior Research Methods 48(3), 1047-1061. DOI: 10.3758/s13428-015-0629-5.

Zhivan, N.A., Ang, A., Amaro, H. et al. (2012) Ethnic/race differences in the attrition of older American survey respondents: Implications for health-related research. Health Services Research 47(1), 241-254. DOI: 10.1111/j.1475-6773.2011.01322.x.