Journal articles: 'Longitudinal survey'

1

Hiskey, Syd, and Nicholas A. Troop. "Online Longitudinal Survey Research." Social Science Computer Review 20, no. 3 (August 2002): 250–59. http://dx.doi.org/10.1177/089443930202000303.

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2

Hawke, Anne. "The Business Longitudinal Survey." Australian Economic Review 33, no. 1 (March 2000): 94–99. http://dx.doi.org/10.1111/1467-8462.00140.

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3

Yates, Julie A., and Donna S. Rothstein. "The Newest National Longitudinal Survey: The National Longitudinal Survey of Youth, 1997." Industrial Relations: A Journal of Economy and Society 38, no. 4 (October 1999): 604–10. http://dx.doi.org/10.1111/0019-8676.00147.

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4

YOSHIOKA, Yosuke. "Use of Internet Longitudinal Survey." Japanese Sociological Review 71, no. 1 (2020): 50–64. http://dx.doi.org/10.4057/jsr.71.50.

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5

Thompson, Mary E. "Using Longitudinal Complex Survey Data." Annual Review of Statistics and Its Application 2, no. 1 (April 10, 2015): 305–20. http://dx.doi.org/10.1146/annurev-statistics-010814-020403.

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6

Titma, Mikk, Brian D. Silver, Rein Vöörmann, and Douglas Johnson. "4 The Estonian Longitudinal Survey." International Journal of Sociology 26, no. 1 (March 1996): 76–93. http://dx.doi.org/10.1080/15579336.1996.11770135.

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7

Loxton, Deborah, and Anne Young. "Longitudinal survey development and design." International Journal of Multiple Research Approaches 1, no. 2 (December 2007): 114–25. http://dx.doi.org/10.5172/mra.455.1.2.114.

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8

Tozer, Clem. "The Australian Business Longitudinal Survey." Small Enterprise Research 5, no. 1 (January 1997): 16–28. http://dx.doi.org/10.5172/ser.5.1.16.

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9

Miller, Paul W. "The Australian Longitudinal Survey and the Australian Youth Survey." Australian Economic Review 28, no. 1 (January 1995): 123–29. http://dx.doi.org/10.1111/j.1467-8462.1995.tb00881.x.

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10

Alderman, Harold, Jere Behrman, Susan Watkins, Hans-Peter Kohler, and John A. Maluccio. "Attrition in Longitudinal Household Survey Data." Demographic Research 5 (November 13, 2001): 79–124. http://dx.doi.org/10.4054/demres.2001.5.4.

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11

Petrie, D. Bruce. "Canada's National Longitudinal Survey of Children." Statistical Journal of the United Nations Economic Commission for Europe 12, no. 3-4 (October 1, 1995): 289–97. http://dx.doi.org/10.3233/sju-1995-123-407.

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12

Pergamit, Michael R., Charles R. Pierret, Donna S. Rothstein, and Jonathan R. Veum. "Data Watch: The National Longitudinal Surveys." Journal of Economic Perspectives 15, no. 2 (May 1, 2001): 239–53. http://dx.doi.org/10.1257/jep.15.2.239.

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This article describes the design features and topical coverage of the National Longitudinal Surveys (NLS). The NLS are perhaps the oldest and most widely used panel surveys of individuals in the United States. These surveys were started in the mid-1960s to exam employment issues faced by different cohorts of the U.S. population. Since then, the NLS surveys have expanded to include two new cohorts of youth. Survey topic areas include employment, education, training, family relationships, financial well-being, and health. Information on data access is also provided.

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13

Mavletova, Aigul. "A Gamification Effect in Longitudinal Web Surveys among Children and Adolescents." International Journal of Market Research 57, no. 3 (May 2015): 413–38. http://dx.doi.org/10.2501/ijmr-2015-035.

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The paper measures a gamification effect in longitudinal web surveys among children and adolescents 7–15 years old. Two waves of the study were conducted using a volunteer online access panel in Russia among 737 children. Respondents were randomly assigned to one of the three conditions in the first wave without changing the treatment in the second wave: (1) a text-only survey, (2) a visual survey and (3) a gamified survey. Though in the first wave of the study respondents found it more enjoyable and easier to complete the gamified survey, no differences in participation rates were found between the conditions in the second wave. Contrary to expectations, a higher breakoff was found in the gamified condition. Moreover, it produced lower test-retest reliability correlations than the text-only and visual conditions in all survey questions. The promising gamification effect found in the first wave of the study faded in the second wave. It seems that implementing gamified elements in longitudinal web surveys might differ from the implementation of gamified elements in cross-sectional surveys.

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Pyeye, Sarah, Charles K. Syengo, Leo Odongo, George O. Orwa, and Romanus O. Odhiambo. "Longitudinal Survey, Nonmonotone, Nonresponse, Imputation, Nonparametric Regression." Open Journal of Statistics 06, no. 06 (2016): 1138–54. http://dx.doi.org/10.4236/ojs.2016.66092.

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15

Zhang, Q. M., P. F. Chen, C. Xia, R. Keppens, and H. S. Ji. "Parametric survey of longitudinal prominence oscillation simulations." Astronomy & Astrophysics 554 (June 2013): A124. http://dx.doi.org/10.1051/0004-6361/201220705.

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16

Zhang, Guoyi, Yang Cheng, and Yan Lu. "Generalised variance functions for longitudinal survey data." Statistical Theory and Related Fields 3, no. 2 (July 3, 2019): 150–57. http://dx.doi.org/10.1080/24754269.2019.1664372.

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17

Rechichi, Caterina, and Luigi Scullica. "VDU work: longitudinal survey on refractive defects." Acta Ophthalmologica Scandinavica 74, no. 6 (May 27, 2009): 629–31. http://dx.doi.org/10.1111/j.1600-0420.1996.tb00750.x.

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18

Hilmola, Olli‐Pekka, and Harri Lorentz. "Warehousing in Northern Europe: longitudinal survey findings." Industrial Management & Data Systems 111, no. 3 (March 22, 2011): 320–40. http://dx.doi.org/10.1108/02635571111118242.

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19

Golding, Jean, Richard Jones, Marie-Noël Bruné, and Jenny Pronczuk. "Why carry out a longitudinal birth survey?" Paediatric and Perinatal Epidemiology 23 (July 2009): 1–14. http://dx.doi.org/10.1111/j.1365-3016.2008.01009.x.

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20

Cobb-Clark, Deborah. "The Longitudinal Survey of Immigrants to Australia." Australian Economic Review 34, no. 4 (December 2001): 467–77. http://dx.doi.org/10.1111/1467-8462.00216.

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21

Allur, Erlantz, Iñaki Heras-Saizarbitoria, and Martí Casadesús. "Internalization of ISO 9001: a longitudinal survey." Industrial Management & Data Systems 114, no. 6 (June 3, 2014): 872–85. http://dx.doi.org/10.1108/imds-01-2014-0013.

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Purpose – The purpose of this paper is to analyze the influence of the motivation to adopt International Standards Organization (ISO) 9001 on both the internalization of the standard, namely the active day-to-day use of its main underlying practices, and the benefits obtained from its adoption. Similarly, the influence of the internalization on the benefits derived from ISO 9001 is analyzed. Design/methodology/approach – A longitudinal survey was carried out on a sample of 110 Spanish organizations that adopted the standard in its early phase of dissemination. These organizations were surveyed in 1999 and, 12 years later, in 2011. Findings – The results show that, contrary to the results of previous research work, early adopters driven by internal motives experience neither higher levels of internalization of ISO 9001 nor higher benefits from adoption of the standard. Nevertheless, there is clear evidence that in the long run a higher level of internalization leads to greater benefits from the adoption of ISO 9001. Originality/value – The adoption of ISO 9001 is a dynamic process in which certificating organizations play an important role.

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22

Pike, Richard. "A LONGITUDINAL SURVEY ON CAPITAL BUDGETING PRACTICES." Journal of Business Finance & Accounting 23, no. 1 (January 1996): 79–92. http://dx.doi.org/10.1111/j.1468-5957.1996.tb00403.x.

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23

Büttner, Tobias J. M., Joseph W. Sakshaug, and Basha Vicari. "Evaluating the Utility of Linked Administrative Data for Nonresponse Bias Adjustment in a Piggyback Longitudinal Survey." Journal of Official Statistics 37, no. 4 (December 1, 2021): 837–64. http://dx.doi.org/10.2478/jos-2021-0037.

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Abstract Nearly all panel surveys suffer from unit nonresponse and the risk of nonresponse bias. Just as the analytic value of panel surveys increase with their length, so does cumulative attrition, which can adversely affect the representativeness of the resulting survey estimates. Auxiliary data can be useful for monitoring and adjusting for attrition bias, but traditional auxiliary sources have known limitations. We investigate the utility of linked-administrative data to adjust for attrition bias in a standard piggyback longitudinal design, where respondents from a preceding general population cross-sectional survey, which included a data linkage request, were recruited for a subsequent longitudinal survey. Using the linked-administrative data from the preceding survey, we estimate attrition biases for the first eight study waves of the longitudinal survey and investigate whether an augmented weighting scheme that incorporates the linked-administrative data reduces attrition biases. We find that adding the administrative information to the weighting scheme generally leads to a modest reduction in attrition bias compared to a standard weighting procedure and, in some cases, reduces variation in the point estimates. We conclude with a discussion of these results and remark on the practical implications of incorporating linked-administrative data in piggyback longitudinal designs.

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24

Krueger, Kurt V., and Gary R. Skoog. "Transitions Into and Out of Census Disability." Journal of Forensic Economics 26, no. 1 (December 1, 2015): 17–51. http://dx.doi.org/10.5085/0898-5510-26.1.17.

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Abstract This paper examines disability as measured and reported in three Census surveys: the American Community Survey (ACS), the Current Population Survey (CPS), and the Survey on Income Program Participation (SIPP). We focus on whether person-specific disability, as measured by the Census, is a permanent or a transitory condition. Survey data results regarding the incidence of Census-measured disability are shown both cross-sectionally and longitudinally. It is found from longitudinal CPS and SIPP responses that Census-measured disability is largely transitory. That finding empirically confirms the longstanding theoretical objections to the use of Census cross-section disability data along with a permanent disability assumption in worklife expectancy models; hence, any worklife expectancy model which assumes that Census disability measures are permanent conditions is misspecified and empirically invalid. Instead of using the permanent disability assumption, we use actual longitudinal disability transition probabilities and life table analysis to quantify the lifetime duration of disability as measured by the Census in total life years and working life years. We show that the realistic feature of disability transition dramatically lowers the effect of disability on worklife expectancy.

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25

Webber, Maryanne. "Disseminating Data From Longitudinal Surveys: Issues Facing the Survey of Labour and Income Dynamics." IASSIST Quarterly 19, no. 2 (October 31, 1995): 36. http://dx.doi.org/10.29173/iq709.

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26

Brakenhoff, Brittany, Bohyun Jang, Natasha Slesnick, and Anastasia Snyder. "Longitudinal predictors of homelessness: findings from the National Longitudinal Survey of Youth-97." Journal of Youth Studies 18, no. 8 (March 24, 2015): 1015–34. http://dx.doi.org/10.1080/13676261.2015.1020930.

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27

Bjarnason, Thoroddur, and Sigrun Adalbjarnardottir. "Anonymity and Confidentiality in School Surveys on Alcohol, Tobacco, and Cannabis Use." Journal of Drug Issues 30, no. 2 (April 2000): 335–43. http://dx.doi.org/10.1177/002204260003000206.

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School surveys are currently the most important method of collecting data on alcohol and drug use among youth. Although methodological studies suggest that school surveys yield reliable and valid estimates of substance use among youth, it has been argued that results will be affected by the level of perceived anonymity. Longitudinal research designs raise an important question in this respect since follow-up makes complete anonymity impossible. In fact, responses to such surveys should be regarded as confidential rather than anonymous. This study compares the reported use of cigarettes, alcohol and cannabis between an anonymous, cross-sectional survey and a confidential, longitudinal survey. Both females and males in the confidential survey have a slightly higher rate of non-response for lifetime cannabis use. Furthermore, females tend to be slightly less likely to admit to any use of alcohol and cannabis in the confidential survey, and those who do admit to having used cigarettes and alcohol, report slightly fewer occasions. The correlations between use of cigarettes, alcohol, and cannabis are not affected by this bias. These results add further support to earlier research that has found school surveys to be a robust method of data collection, and suggests that the bias introduced by identification numbers in longitudinal research has limited practical significance.

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28

Michael, Robert T., and Michael R. Pergamit. "The National Longitudinal Survey of Youth, 1997 Cohort." Journal of Human Resources 36, no. 4 (2001): 628. http://dx.doi.org/10.2307/3069636.

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29

Cohen, Steven B., Fred Rohde, and William Yu. "Building Wave Response Rates in a Longitudinal Survey." Field Methods 25, no. 4 (October 17, 2013): 361–87. http://dx.doi.org/10.1177/1525822x13507863.

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30

Orr, Stuart C. "A longitudinal survey of robot usage in Australia." Integrated Manufacturing Systems 7, no. 5 (October 1996): 33–46. http://dx.doi.org/10.1108/09576069610129900.

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31

Wang, Li, Suojin Wang, and Guannan Wang. "Variable selection and estimation for longitudinal survey data." Journal of Multivariate Analysis 130 (September 2014): 409–24. http://dx.doi.org/10.1016/j.jmva.2014.05.006.

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32

Lewis, Phillip V. "Ethical principles for decision makers: A longitudinal survey." Journal of Business Ethics 8, no. 4 (April 1989): 271–78. http://dx.doi.org/10.1007/bf00383341.

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33

François, Martine, Annie Dumont, and Philippe Narcy. "Longitudinal survey of voice quality after pediatric laryngotracheoplasty." International Journal of Pediatric Otorhinolaryngology 40, no. 2-3 (June 1997): 163–72. http://dx.doi.org/10.1016/s0165-5876(97)00046-3.

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34

Zeng, Yi, and Zhenzhen Zheng. "Longitudinal survey and interdisciplinary research on healthy aging." China Population and Development Studies 3, no. 4 (March 11, 2020): 293–96. http://dx.doi.org/10.1007/s42379-020-00051-9.

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35

Tesfaye, A., and M. Martin Curran. "A Longitudinal Survey of Market Donkeys in Ethiopia." Tropical Animal Health and Production 37, S1 (January 2005): 87–100. http://dx.doi.org/10.1007/s11250-005-9010-5.

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36

Smith, Paul A., and Wesley Yung. "A review and evaluation of the use of longitudinal approaches in business surveys." Longitudinal and Life Course Studies 10, no. 4 (October 1, 2019): 491–511. http://dx.doi.org/10.1332/175795919x15694142999134.

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Business surveys are not generally considered to be longitudinal by design. However, the largest businesses are almost always included in each wave of recurrent surveys because they are essential for producing good estimates; and short-period business surveys frequently make use of rotating panel designs to improve the estimates of change by inducing sample overlaps between different periods. These design features mean that business surveys share some methodological challenges with longitudinal surveys. We review the longitudinal methods and approaches that can be used to improve the design and operation of business surveys, giving examples of their use. We also look in the other direction, considering the aspects of longitudinal analysis that have the potential to improve the accuracy, relevance and interpretation of business survey outputs.

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37

Konold, Tim R., Kelly D. Edwards, and Dewey G. Cornell. "Longitudinal Measurement Invariance of the Authoritative School Climate Survey." Journal of Psychoeducational Assessment 39, no. 6 (April 21, 2021): 651–64. http://dx.doi.org/10.1177/07342829211011332.

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This study evaluated the longitudinal psychometric properties of the Authoritative School Climate Survey (ASCS) using a statewide sample of middle and high schools across 8 years. Multilevel confirmatory factor analyses were conducted to test the longitudinal measurement invariance of three scales on the ASCS: disciplinary structure, teacher respect for students, and students’ willingness to seek help. These scales demonstrated strong factorial invariance across all time points for both middle and high schools. Results support the use of these scales in evaluating longitudinal change in school climate.

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38

Johnson, David S., Catherine Massey, and Amy O’Hara. "The Opportunities and Challenges of Using Administrative Data Linkages to Evaluate Mobility." ANNALS of the American Academy of Political and Social Science 657, no. 1 (December 10, 2014): 247–64. http://dx.doi.org/10.1177/0002716214552780.

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Since Alan Krueger’s christening of the Great Gatsby curve, there has been increased attention given to the relationship between inequality and intergenerational social mobility in the United States. Studying intergenerational mobility (IGM) requires longitudinal data across large spans of time as well as the ability to follow parents and children over multiple generations. Few longitudinal datasets meet this need. This article surveys available data and the current and potential issues surrounding the use of administrative records to vastly extend the study of IGM. First, we describe the U.S. Census Bureau’s current uses of administrative records in the linkage of households across household surveys such as the Current Population Survey (CPS), American Community Survey (ACS), Survey of Income and Program Participation (SIPP), and the decennial censuses. Then, we describe the possibilities of creating additional parent-child linkages using the SIPP linked to decennial censuses and the ACS. Last, we outline our model to create linkages across earlier census data (e.g., 1980 and 1990) and contemporary surveys.

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39

Yoshino, Ryozo. "Trust and National Character: Japanese Sense of Trust, Cross-National and Longitudinal Surveys." Comparative Sociology 4, no. 3-4 (2005): 417–50. http://dx.doi.org/10.1163/156913305775010142.

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AbstractThis paper overviews people's sense of trust as it is reflected in the response data of questionnaire surveys. I will study the variability of people's trust systems in order to explore the stability over time and the change due to the short-term changes of economic and political conditions. To begin with, I will explain briefly the history of our longitudinal and cross-national survey on national character. Secondly, I will summarize some aspects of people's sense of trust in our longitudinal survey of Japanese national character. Thirdly, I will present cross-national comparative analysis of trust in our seven-country survey and our East Asia survey. Fourthly, I will consider the acculturation of the Japanese immigrants in Brazil, Hawaii, and the West Coast of USA. Finally, I will provide some comments on cross-national scaling of trust for our future research.

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40

Earp, Morgan, Daniell Toth, Polly Phipps, and Charlotte Oslund. "Assessing Nonresponse in a Longitudinal Establishment Survey Using Regression Trees." Journal of Official Statistics 34, no. 2 (June 1, 2018): 463–81. http://dx.doi.org/10.2478/jos-2018-0021.

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Abstract This article introduces and discusses a method for conducting an analysis of nonresponse for a longitudinal establishment survey using regression trees. The methodology consists of three parts: analysis during the frame refinement and enrollment phases, common in longitudinal surveys; analysis of the effect of time on response rates during data collection; and analysis of the potential for nonresponse bias. For all three analyses, regression tree models are used to identify establishment characteristics and subgroups of establishments that represent vulnerabilities during the data collection process. This information could be used to direct additional resources to collecting data from identified establishments in order to improve the response rate.

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41

Mooney, Geraldine M., Melissa Krakowiecki, and Deborah Trunzo. "Does Prefilling Questions in a Longitudinal Survey Encourage Participation?" Survey Practice 3, no. 2 (April 1, 2010): 1–5. http://dx.doi.org/10.29115/sp-2010-0008.

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42

Nakashima, Makoto, Katsuro Mamitsuka, Junko Kai, Tadashi Sugiyama, and Hideki Hayashi. "Longitudinal Survey of Polypharmacy in a Palliative Care Unit." Iryo Yakugaku (Japanese Journal of Pharmaceutical Health Care and Sciences) 46, no. 10 (October 10, 2020): 551–60. http://dx.doi.org/10.5649/jjphcs.46.551.

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43

Jennings, M. Kent, and Gregory B. Markus. "Political Involvement in the Later Years: A Longitudinal Survey." American Journal of Political Science 32, no. 2 (May 1988): 302. http://dx.doi.org/10.2307/2111125.

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44

Chavarria, Juan A., Francis Kofi Andoh-Baidoo, Vishal Midha, and Jerald Hughes. "Software Piracy Research: A Cross Disciplinary Longitudinal Literature Survey." Communications of the Association for Information Systems 38 (2016): 624–69. http://dx.doi.org/10.17705/1cais.03831.

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45

Jacobson, Sharol F., and Karen F. Jordan. "Nrses' Reasons for Participating in a Longitudinal Panel Survey." Western Journal of Nursing Research 15, no. 4 (August 1993): 509–15. http://dx.doi.org/10.1177/019394599301500410.

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46

Kleinpell-Nowell, Ruth. "Longitudinal Survey of Acute Care Nurse Practitioner Practice: Yearl." AACN Clinical Issues: Advanced Practice in Acute and Critical Care 10, no. 4 (November 1999): 515–20. http://dx.doi.org/10.1097/00044067-199911000-00012.

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47

Chiswick, Barry R., Yew Liang Lee, and Paul W. Miller. "Patterns of Immigrant Occupational Attainment in a Longitudinal Survey." International Migration 41, no. 4 (October 2003): 47–69. http://dx.doi.org/10.1111/1468-2435.00252.

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48

Zeng, Yi. "Chinese Longitudinal Healthy Longevity Survey and some research findings." Geriatrics and Gerontology International 4, s1 (September 2004): S49—S52. http://dx.doi.org/10.1111/j.1447-0594.2004.00147.x.

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49

Ran, Mao-Sheng, Xue Weng, Yu-Jun Liu, Tian-Ming Zhang, Graham Thornicroft, Larry Davidson, Cheryl H. K. Chui, et al. "Severe mental disorders in rural China: a longitudinal survey." Lancet 390 (December 2017): S37. http://dx.doi.org/10.1016/s0140-6736(17)33175-6.

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50

Sutradhar, B. C. "Analysing ordinal longitudinal survey data: Generalised estimating equations approach." Biometrika 87, no. 4 (December 1, 2000): 837–48. http://dx.doi.org/10.1093/biomet/87.4.837.

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Journal articles on the topic 'Longitudinal survey'

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