Papers - Erik Meijer

Journal articles

Lee, J., et al. (2023). Prevalence of dementia in India: National and state estimates from a nationwide study. Alzheimer’s & Dementia. (in press)

Lee, J., et al. (2023). The LASI-DAD, deep phenotyping and genomic data for study of cognition and dementia in India. Scientific Data. (in press)

Junghaenel, D. U., et al. (2023). Inferring cognitive abilities from response times to web-administered survey items in a population-representative sample. Journal of Intelligence, 11(1), 3. https://doi.org/10.3390/jintelligence11010003

Gatz, M., Schneider, S., Meijer, E., Darling, J. E., Orriens, B., Liu, Y., & Kapteyn, A. (2022). Identifying cognitive impairment among older participants in a nationally representative internet panel. Journals of Gerontology: Psychological Sciences. https://doi.org/10.1093/geronb/gbac172

Khobragade, P., Nichols, E., Meijer, E., Varghese, M., Banerjee, J., Dey, A. B., … Ganguli, M. (2022). Performance of the Informant Questionnaire on Cognitive Decline for the Elderly (IQCODE) in a nationally representative study in India: The LASI-DAD study. International Psychogeriatrics. https://doi.org/10.1017/S1041610222000606

Meijer, E., Casanova, M., Kim, H., Llena-Nozal, A., & Lee, J. (2022). Economic costs of dementia in 11 countries in Europe: Estimates from nationally representative cohorts of a panel study. The Lancet Regional Health – Europe, 20, 100445. https://doi.org/10.1016/j.lanepe.2022.100445

Schneider, S., Junghaenel, D. U., Meijer, E., Zelinski, E. M., Jin, H., Lee, P.-J., & Stone, A. A. (2022). Quality of survey responses at older ages predicts cognitive decline and mortality risk. Innovation in Aging, 6(3), 1–11. https://doi.org/10.1093/geroni/igac027

Schneider, S., Jin, H., Orriens, B., Junghaenel, D. U., Kapteyn, A., Meijer, E., & Stone, A. A. (2022). Using attributes of survey items to predict response times may benefit survey research. Field Methods. https://doi.org/10.1177/1525822X221100904

Liu, Y., Schneider, S., Orriens, B., Meijer, E., Darling, J. E., Gutsche, T., & Gatz, M. (2022). Self-administered web-based tests of executive functioning and perceptual speed: Measurement development study with a large probability-based survey panel. Journal of Medical Internet Research, 24(5), e34347. https://doi.org/10.2196/34347

Meijer, E., Spierdijk, L., & Wansbeek, T. (2022). Moment conditions for the quadratic regression model with measurement error. Econometric Reviews, 41, 749–774. https://doi.org/10.1080/07474938.2022.2052666

Lee, J., Wilkens, J., Meijer, E., Sekher, T. V., Bloom, D. E., & Hu, P. (2022). Hypertension awareness, treatment, and control and their association with healthcare access in the middle-aged and older Indian population: A nationwide cohort study. PLoS Medicine, 19(1), e1003855. https://doi.org/10.1371/journal.pmed.1003855

Schneider, S., Junghaenel, D. U., Zelinski, E. M., Meijer, E., Stone, A. A., Langa, K. M., & Kapteyn, A. (2021). Subtle mistakes in self-report surveys predict future transition to dementia. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 13(1), e12252. https://doi.org/10.1002/dad2.12252

Jung, D., Lee, J., & Meijer, E. (2021). Revisiting the effect of retirement on cognition: Heterogeneity and endowment. Journal of the Economics of Ageing, 21, 100361. https://doi.org/10.1016/j.jeoa.2021.100361

Jin, H., Chien, S., Meijer, E., Khobragade, P., & Lee, J. (2021). Learning from clinical consensus diagnosis in India to facilitate automatic classification of dementia: Machine learning study. JMIR Mental Health, 8(5), e27113. https://doi.org/10.2196/27113

Lee, J., Meijer, E., Phillips, D., & Hu, P. (2021). Disability incidence rates for men and women in 23 countries: Evidence on health effects of gender inequality. Journals of Gerontology: Medical Sciences, 76, 328–338. https://doi.org/10.1093/gerona/glaa288

Meijer, E., Oczkowski, E., & Wansbeek, T. (2021). How measurement error affects inference in linear regression. Empirical Economics, 60, 131–155. https://doi.org/10.1007/s00181-020-01942-z

Angrisani, M., Lee, J., & Meijer, E. (2020). The gender gap in education and late-life cognition: Evidence from multiple countries and birth cohorts. Journal of the Economics of Ageing, 16, 100232. https://doi.org/10.1016/j.jeoa.2019.100232

Gross, A. L., Khobragade, P. Y., Meijer, E., & Saxton, J. A. (2020). Measurement and structure of cognition in the Longitudinal Aging Study in India – Diagnostic Assessment of Dementia (LASI-DAD). Journal of the American Geriatrics Society, 68, S11–S19. https://doi.org/10.1111/jgs.16738

Angrisani, M., Casanova, M., & Meijer, E. (2020). Work-life balance and labor force attachment at older ages. Journal of Labor Research, 41, 34–68. https://doi.org/10.1007/s12122-020-09301-8

Kapteyn, A., et al. (2020). Tracking the effect of the COVID-19 pandemic on American households. Survey Research Methods, 14(2), 179–186. https://doi.org/10.18148/srm/2020.v14i2.7737

Lee, J., Lau, S., Meijer, E., & Hu, P. (2020). Living longer, with or without disability? A global and longitudinal perspective. Journals of Gerontology: Medical Sciences, 75(1), 162–167. https://doi.org/10.1093/gerona/glz007

Hurd, M. D., Meijer, E., Moldoff, M., & Rohwedder, S. (2019). Reducing cross-wave variability in survey measures of household wealth. Journal of Economic and Social Measurement, 44, 117–139. https://doi.org/10.3233/JEM-190465

Galesic, M., Bruine de Bruin, W., Dumas, M., Kapteyn, A., Darling, J. E., & Meijer, E. (2018). Asking about social circles improves election predictions and illuminates voting behaviour. Nature Human Behaviour, 2, 187–193. https://doi.org/10.1038/s41562-018-0302-y

Meijer, E., Spierdijk, L., & Wansbeek, T. (2017). Consistent estimation of linear panel data models with measurement error. Journal of Econometrics, 200, 169–180. https://doi.org/10.1016/j.jeconom.2017.06.003

Meijer, E., & Karoly, L. A. (2017). Representativeness of the low-income population in the Health and Retirement Study. Journal of the Economics of Ageing, 9, 90–99. https://doi.org/10.1016/j.jeoa.2016.08.004

Angrisani, M., Hurd, M. D., Meijer, E., Parker, A. M., & Rohwedder, S. (2017). Personality and employment transitions at older ages: Direct and indirect effects through non-monetary job characteristics. Labour, 31, 127–152. https://doi.org/10.1111/labr.12090

Gutsche, T. L., Kapteyn, A., Meijer, E., & Weerman, B. (2014). The RAND Continuous 2012 Presidential Election Poll. Public Opinion Quarterly, 78, 233–254. https://doi.org/10.1093/poq/nfu009

Galama, T. J., Hullegie, P., Meijer, E., & Outcault, S. (2012). Is there empirical evidence for decreasing returns to scale in a health capital model? Health Economics, 21, 1080–1100. PMCID: PMC3412934; https://doi.org/10.1002/hec.2843

Meijer, E., Rohwedder, S., & Wansbeek, T. (2012). Measurement error in earnings data: Using a mixture model approach to combine survey and register data. Journal of Business & Economic Statistics, 30, 191–201. PMCID: PMC3604906; https://doi.org/10.1198/jbes.2011.08166

Meijer, E., Kapteyn, A., & Andreyeva, T. (2011). Internationally comparable health indices. Health Economics, 20, 600–619. PMCID: PMC3601939; https://doi.org/10.1002/hec.1620

Meijer, E., Karoly, L. A., & Michaud, P.-C. (2010). Using matched survey and administrative data to estimate eligibility for the Medicare Part D low-income subsidy program. Social Security Bulletin, 70(2), 63–82. http://www.socialsecurity.gov/policy/docs/ssb/v70n2/

Meijer, E., & Ypma, J. Y. (2008). A simple identification proof for a mixture of two univariate normal distributions. Journal of Classification, 25, 113–123. https://doi.org/10.1007/s00357-008-9008-6

Wansbeek, T., & Meijer, E. (2007). Comments on: Panel data analysis—advantages and challenges. Test, 16, 33–36. https://doi.org/10.1007/s11749-007-0050-1

Meijer, E., & Wansbeek, T. (2007). The sample selection model from a method of moments perspective. Econometric Reviews, 26, 25–51. https://doi.org/10.1080/07474930600972194

Meijer, E. (2007). Citations, reference list, and author index with apacite. Eutypon, 16–19, 1–31. http://www.eutypon.gr/eutypon/e-cont-16-19.html

Meijer, E., & Rouwendal, J. (2006). Measuring welfare effects in models with random coefficients. Journal of Applied Econometrics, 21, 227–244. https://doi.org/10.1002/jae.841

Meijer, E. (2005). Matrix algebra for higher order moments. Linear Algebra and its Applications, 410, 112–134. https://doi.org/10.1016/j.laa.2005.02.040

De Haan, J., Leertouwer, E., Meijer, E., & Wansbeek, T. (2003). Measuring central bank independence: A latent variables approach. Scottish Journal of Political Economy, 50, 326–340. https://doi.org/10.1111/1467-9485.5003005

Rouwendal, J., & Meijer, E. (2001). Preferences for housing, jobs, and commuting: A mixed logit analysis. Journal of Regional Science, 41, 475–505. https://doi.org/10.1111/0022-4146.00227

Wansbeek, T., Wedel, M., & Meijer, E. (2001). Comment on Microeconometrics by J.A. Hausman. Journal of Econometrics, 100, 89–91. https://doi.org/10.1016/S0304-4076(00)00065-8

Meijer, E., & Wansbeek, T. (2000). Measurement error in a single regressor. Economics Letters, 69, 277–284. https://doi.org/10.1016/S0165-1765(00)00328-1

Meijer, E., & Wansbeek, T. (1999). Quadratic prediction of factor scores. Psychometrika, 64, 495–507. https://doi.org/10.1007/BF02294569

Busing, F. M. T. A., Meijer, E., & Van der Leeden, R. (1999). Delete-m jackknife for unequal m. Statistics and Computing, 9, 3–8. https://doi.org/10.1023/A:1008800423698

Meijer, E., & Mooijaart, A. (1996). Factor analysis with heteroscedastic errors. British Journal of Mathematical and Statistical Psychology, 49, 189–202. https://doi.org/10.1111/j.2044-8317.1996.tb01082.x

Meijer, E., & Mooijaart, A. (1994). The use of third-order moments in structural models. Qüestiió, 18, 75–84. http://www.idescat.cat/sort/questiio/sumaris/sum181.html

Book chapters

Meijer, E., Spierdijk, L., & Wansbeek, T. (2015). Measurement error in panel data. In B. H. Baltagi (Ed.), The Oxford handbook of panel data (pp. 325–362). Oxford, UK: Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199940042.013.0011

Kapteyn, A., & Meijer, E. (2014). A comparison of different measures of health and their relation to labor force transitions at older ages. In D. A. Wise (Ed.), Discoveries in the economics of aging (pp. 115–156). Chicago, IL: University of Chicago Press. (with a comment by S. F. Venti) https://doi.org/10.7208/chicago/9780226146126.003.0004

Meijer, E., Spierdijk, L., & Wansbeek, T. (2013). Measurement error in the linear dynamic panel data model. In B. C. Sutradhar (Ed.), ISS-2012 proceedings volume on longitudinal data analysis subject to measurement error, missing values and/or outliers (pp. 77–92). New York, NY: Springer. https://doi.org/10.1007/978-1-4614-6871-4_4

Fernandes, M., Meijer, E., & Zamarro, G. (2008). Comparison between SHARE, ELSA, and HRS. In A. Börsch-Supan et al. (Eds.), Health, ageing and retirement in Europe (2004–2007): Starting the longitudinal dimension (pp. 23–63). Mannheim, Germany: Mannheim Research Institute for the Economics of Aging (MEA). http://www.share-project.org/publications/books0/first-results-books.html

De Leeuw, J., & Meijer, E. (2008). Introduction to multilevel analysis. In J. de Leeuw & E. Meijer (Eds.), Handbook of multilevel analysis (pp. 1–75). New York, NY: Springer. https://doi.org/10.1007/978-0-387-73186-5_1

Van der Leeden, R., Meijer, E., & Busing, F. M. T. A. (2008). Resampling multilevel models. In J. de Leeuw & E. Meijer (Eds.), Handbook of multilevel analysis (pp. 401–433). New York, NY: Springer. https://doi.org/10.1007/978-0-387-73186-5_11

Wansbeek, T., & Meijer, E. (2001). Measurement error and latent variables. In B. H. Baltagi (Ed.), A companion to theoretical econometrics (pp. 162–179). Malden, MA: Blackwell. https://doi.org/10.1002/9780470996249.ch9

Meijer, E., Busing, F. M. T. A., & Van der Leeden, R. (1998). Estimating bootstrap confidence intervals for two-level models. In J. J. Hox & E. D. De Leeuw (Eds.), Assumptions,robustness, and estimation methods in multivariate modeling (pp. 35–47). Amsterdam, Netherlands: TT Publicaties.

Busing, F. M. T. A., Meijer, E., & Van der Leeden, R. (1995). The MLA program for two-level analysis with resampling options. In T. A. B. Snijders, B. Engel, J. C. van Houwelingen, A. Keen, G. J. Stemerdink, & M. Verbeek (Eds.), SSS’95: Toeval zit overal (pp. 37–58). Groningen, Netherlands: iec ProGAMMA.

Books

De Leeuw, J., & Meijer, E. (Eds.). (2008). Handbook of multilevel analysis. New York, NY: Springer. https://doi.org/10.1007/978-0-387-73186-5

Wansbeek, T., & Meijer, E. (2000). Measurement error and latent variables in econometrics. Amsterdam, Netherlands: North-Holland. Available from Amazon

Meijer, E. (1998). Structural equation models for nonnormal data. Leiden, Netherlands: DSWO Press.

Reports

Bugliari, D., et al. (2022). RAND HRS detailed imputations file 2018 (v2) documentation. Santa Monica, CA: RAND Corporation, Center for the Study of Aging. http://hrsonline.isr.umich.edu/modules/meta/rand/index.html (Also earlier versions under slightly different names [2013–2021])

Bugliari, D., et al. (2022). RAND HRS longitudinal file 2018 (v2) documentation. Santa Monica, CA: RAND Corporation, Center for the Study of Aging. http://hrsonline.isr.umich.edu/modules/meta/rand/index.html (Also earlier versions under slightly different names [2013–2021])

Chien, S., et al. (2021). Harmonized LASI-DAD documentation, version A.3. Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https://g2aging.org (Also earlier versions [2020–2021])

Chien, S., et al. (2021). Harmonized ELSA-HCAP documentation, version A. Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https://g2aging.org

Chien, S., et al. (2021). Harmonized HRS-HCAP documentation, version A. Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https://g2aging.org

Chien, S., Young, C., Phillips, D., Wilkens, J., Meijer, E., Angrisani, M., & Lee, J. (2021). Harmonized LASI documentation, version A.2 (2017–2019). Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https://g2aging.org

LASI Investigators. (2021). User guide for 2017–2019 Longitudinal Aging Study in India (LASI) wave 1. Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https://g2aging.org

Angrisani, M., Kapteyn, A., Meijer, E., & Saw, H.-W. (2019). Sampling and weighting the Understanding America Study (Working Paper No. 2019-004). Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https://doi.org/10.2139/ssrn.3502405

Hurd, M. D., Meijer, E., Pantoja, P., & Rohwedder, S. (2018). Addition to the RAND HRS longitudinal files: IRA withdrawals in the HRS, 2000 to 2014 (Working Paper No. WP 2018-388). Ann Arbor, MI: Michigan Retirement Research Center. https://doi.org/10.2139/ssrn.3337842

Pantoja, P., et al. (2018). RAND HRS tax calculations 2014 (V2) documentation. Santa Monica, CA: RAND Corporation, Center for the Study of Aging. Available from http://hrsonline.isr.umich.edu/modules/meta/rand/index.html (Also an earlier version under a slightly different name [2017])

Beaumaster, S., et al. (2017). Harmonized SHARE documentation, version D.4. Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https://g2aging.org (Also earlier versions [2011–2017])

Sikoki, B., Witoelar, F., Strauss, J., Meijer, E., & Suriastini, W. (2013). IFLS East user’s guide and field report. Yogyakarta, Indonesia: SurveyMETER. http://surveymeter.org/research/3/iflseast

Chien, S., Feeney, K., Liu, J., Meijer, E., & Lee, J. (2013). Harmonized LASI pilot data documentation, version: A (Working Paper No. WR-1018). Santa Monica, CA: RAND Corporation. https://doi.org/10.2139/ssrn.2354660

Kapteyn, A., Meijer, E., & Weerman, B. (2012). Methodology of the RAND Continuous 2012 Presidential Election Poll (Working Paper No. WR-961). RAND Corporation. https://doi.org/10.2139/ssrn.2146149

Foster, K., Meijer, E., Schuh, S., & Zabek, M. A. (2011). The 2009 Survey of Consumer Payment Choice (Public Policy Discussion Paper No. 11-01). Federal Reserve Bank of Boston. https://doi.org/10.2139/ssrn.1864854

Lee, J., Kapteyn, A., Meijer, E., & Yang, J.-S. (2010). Pre- and post-retirement asset portfolios (Publication No. 213). Filene Research Institute. http://staging.filene.org/research/report/pre-and-post-retirement-asset-portfolios

Foster, K., Meijer, E., Schuh, S., & Zabek, M. A. (2009). The 2008 Survey of Consumer Payment Choice (Public Policy Discussion Paper No. 09-10). Federal Reserve Bank of Boston. https://doi.org/10.2139/ssrn.1559959

Meijer, E., Karoly, L. A., & Michaud, P.-C. (2009). Estimates of potential eligibility for low-income subsidies under Medicare Part D (Tech. Rep. No. TR-686). RAND Corporation. http://www.rand.org/pubs/technical_reports/TR686/

Meijer, E. (2004). Computation of characteristics of value-of-time distributions and their standard errors (Research Report No. 04F09). University of Groningen, SOM Research School. https://doi.org/10.2139/ssrn.2052669

Busing, F. M. T. A., Meijer, E., & Van der Leeden, R. (1994). MLA: Software for multilevel analysis of data with two levels. User’s guide for version 1.0b (Tech. Rep. No. PRM 94-01). Leiden University, Department of Psychology. (Version 4.1, 2005)

Working papers

Perez-Arce, F., Prados, M., Meijer, E., & Lee, J. (2021). Social Security coverage around the world: The case of China, India and Mexico (Working Paper No. WP 2021-439). Ann Arbor, MI: Michigan Retirement and Disability Research Center. https://mrdrc.isr.umich.edu/publication_types/working-papers/

Meijer, E., Pérez-Arce, F., & Prados, M. (2020). A framework for cost-benefit analysis of totalization agreements (Working Paper No. WP 2020-410). Ann Arbor, MI: Michigan Retirement and Disability Research Center. https://doi.org/10.2139/ssrn.3885782

Angrisani, M., Kapteyn, A., & Meijer, E. (2019). Sorting into jobs and labor supply and demand at older ages (Working Paper). National Bureau of Economic Research. https://doi.org/10.2139/ssrn.3493892

Prados, M. J., Meijer, E., & Pérez-Arce, F. (2019). Macroeconomic effects of social security totalization agreements (Working Paper No. WP 2019-407). Ann Arbor, MI: Michigan Retirement and Disability Research Center. https://doi.org/10.2139/ssrn.3885751

Angrisani, M., Casanova, M., & Meijer, E. (2017). Work-life balance and labor force attachment at older ages (Working Paper No. WP 2017-366). Ann Arbor, MI: Michigan Retirement Research Center. https://doi.org/10.2139/ssrn.3110845

Hurd, M. D., Meijer, E., Moldoff, M., & Rohwedder, S. (2016). Improved wealth measures in the Health and Retirement Study: Asset reconciliation and cross-wave imputation (Working Paper No. WR-1150). Santa Monica, CA: RAND Corporation. https://doi.org/10.2139/ssrn.2791708

Angrisani, M., Kapteyn, A., & Meijer, E. (2015). Nonmonetary job characteristics and employment transitions at older ages (Working Paper No. WP 2015-326). Ann Arbor, MI: Michigan Retirement Research Center. https://doi.org/10.2139/ssrn.2689805

Lee, J., Meijer, E., & Phillips, D. (2015). The effect of using different imputation methods for economic variables in aging surveys (Working Paper No. 2015-019). Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https://doi.org/10.2139/ssrn.2650214

Angrisani, M., Hurd, M. D., & Meijer, E. (2012). Investment decisions in retirement: The role of subjective expectations (Working Paper No. WP 2012-274). Michigan Retirement Research Center. https://doi.org/10.2139/ssrn.2188403

Hung, A. A., Meijer, E., Mihaly, K., & Yoong, J. (2009). Building up, spending down: financial literacy, retirement savings management, and decumulation (Working Paper No. WR-712). RAND Corporation. https://doi.org/10.2139/ssrn.1520203

Gilbert, P. D., & Meijer, E. (2006). Money and credit factors (Working Paper No. 2006-3). Bank of Canada. http://www.bankofcanada.ca/2006/03/publications/research/working-paper-2006-3/

Gilbert, P. D., & Meijer, E. (2005). Time series factor analysis with an application to measuring money (Research Report No. 05F10). University of Groningen, SOM Research School. http://irs.ub.rug.nl/ppn/289322812

Cools, K., Le Grand, H., Meijer, E., & Wansbeek, T. (2004). Solving the value metrics puzzle (Working Paper). University of Groningen, Department of Economics. https://doi.org/10.2139/ssrn.568423

RePEc: http://ideas.repec.org/f/pme236.html

SSRN: http://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=386896

Other publications

Meijer, E., & Wansbeek, T. (2001, 2005). Microeconometrie (Lecture Notes). Groningen, Netherlands: University of Groningen, Faculty of Economics.

Meijer, E. (1999). [Book review of D. A. Harville (1997), Matrix algebra from a statistician’s perspective]. Kwantitatieve Methoden, 20(60), 129–131. (in Dutch)

Rosenberg, F. A., Meurs, H., & Meijer, E. (1997). Grote prijsveranderingen: Een empirische budgetrestrictie-benadering [Large changes in prices: An empirical controlled budget approach]. In B. Egeter & N. Kalfs (Eds.), Colloquium Vervoersplanologisch Speurwerk – 1997 – Sprong in het duister? Lange termijn ontwikkelingen in het vervoersplanologisch onderzoek (pp. 1463–1482). Delft, Netherlands: C.V.S. http://www.cvs-congres.nl/cvspdfdocs/CVS1997deel3C.pdf (in Dutch)

Rosenberg, F. A., Meurs, H., & Meijer, E. (1997). Large changes in prices: An empirical controlled budget approach. In Policy, planning and sustainability: Proceedings of Seminars C and D held at the European Transport Forum Annual Meeting, Brunel University, England, 1–5 September 1997 (pp. 367–378). London: PTRC. http://abstracts.aetransport.org/paper/index/id/548/confid/3

Meurs, H., Meijer, E., & Pommer, J. (1997). No parking, no business? Verkeerskunde, 48(9), 30–34. (in Dutch)

Meurs, H., Meijer, E., & Pommer, J. (1997). Parkeerkwaliteit langs de meetlat [A yardstick for parking quality]. Verkeerskunde, 48(7/8), 30–34. (in Dutch)

Busing, F. M. T. A., Van der Leeden, R., & Meijer, E. (1995). MLA: Software for two-level analysis with resampling options. Multilevel Modelling Newsletter, 7(3), 11–13. http://www.bristol.ac.uk/cmm/learning/support/new7-3.pdf

Meijer, E., Van der Leeden, R., & Busing, F. M. T. A. (1995). Implementing the bootstrap for multilevel models. Multilevel Modelling Newsletter, 7(2), 7–11. http://www.bristol.ac.uk/cmm/learning/support/new7-2.pdf