Please see my CV
for the complete list of publications.
1.
Jackson,
J., Kuha, J., Bradford, B., and Hough, M. (2024). Why do
people cooperate with the police and criminal courts? A test of procedural
justice theory in 30 countries. CrimRxiv
preprint, doi.org/10.21428/cb6ab371.ec343def.
2.
Di Mari, R., Bakk, Z.,
Oser, J., Kuha, J. (2023). Multilevel
latent class analysis with covariates: Analysis of cross-national citizenship
norms with a two-stage approach. arXiv preprint arXiv:2307.10720.
3.
Lyrvall, J., Di Mari, R., Bakk, Z., Oser, J.
and Kuha, J. (2023). multilevLCA: An R package for single-level and multilevel
latent class analysis with covariates. arXiv
preprint arXiv:2305.07276.
4.
Kuha,
J. and Bakk, Z. (2023). Two-step estimation of latent trait models. arXiv preprint arXiv: 2303.16101.
5.
Bosch,
O. J., Sturgis, P., Kuha, J., and
Revilla, M. (2024). Uncovering biases in digital trace data: An assessment of the
prevalence and implications of tracking undercoverage
when using web tracking data. To appear in Communication Methods and
Measures.
6.
Zhang,
S., Kuha, J., and Steele, F. (2024). Modelling correlation matrices in multivariate dyadic data:
Latent variable models for intergenerational exchanges of family support. Annals of Applied Statistics, 18,
3024-3049.
7.
Wouters,
O. J. and Kuha, J. (2024). Low- and middle-income countries experienced delays accessing
new essential medicines, 1982-2024. Health Affairs, 43, 1410-1419.
8.
Wouters, O. J., Kesselheim, A. S., Kuha, J., and Luyten, J. (2024). Sales revenues for new therapeutic agents approved by the US
Food and Drug Administration from 1995 to 2014. Value in Health, 27,
1373-1381.
9.
Di Mari, R., Bakk, Z.,
Oser, J., Kuha, J. (2023). A two-step estimator for multilevel latent class analysis with
covariates. Psychometrika, 88, 1144-1170.
10.
Kuha,
J., Zhang, S., and Steele, F. (2023). Latent variable models for multivariate dyadic data with zero
inflation: Analysis of intergenerational exchanges of family support. Annals
of Applied Statistics, 17, 1521-1542.
11.
Bakk,
Z., Di Mari, R., Oser, J., and Kuha, J. (2022). Two-stage multilevel latent class analysis with covariates in
the presence of direct effects. Structural Equation Modeling,
29, 267-277.
12.
Sturgis,
P. and Kuha, J. (2022). How survey mode affects estimates of the prevalence of gambling
harm: A multi-survey study. Public Health, 204, 63-69.
13.
Kuha,
J., Bukodi, E., and Goldthorpe, J. H. (2021). Mediation analysis for associations of categorical variables: The
role of education in social class mobility in Britain. Annals of Applied
Statistics, 15, 2061-2082.
14.
Burchardt,
T., Steele, F., Grundy, E., Karagiannaki, E., Kuha,
J., Moustaki. I., Skinner C,, Zhang, N., and Zhang,
S. (2021). Welfare within families beyond households: Intergenerational exchanges of practical and
financial support in the UK. LSE Public Policy Review, 2, 4: 1-11.
15.
Bakk,
Z. and Kuha, J. (2021). Relating latent class membership to external variables: An
overview. British Journal of Mathematical and Statistical Psychology,
74, 340-362.
16.
Kuha,
J. and Mills, C. (2020). On group comparisons with logistic regression models. Sociological Methods & Research, 49,
498-525.
17.
Steele,
F., Clarke, P., and Kuha, J. (2019). Modeling within-household
associations in household panel studies. Annals of Applied Statistics, 13, 367-392.
18.
Janssen,
J. H. M., van Laar, S., de Rooij, M. J., Kuha, J.,
and Bakk. Z. (2019). The detection and modeling of direct
effects in latent class analysis. Structural
Equation Modeling, 26, 280-290.
19.
Bakk,
Z. and Kuha, J. (2018). Two-step estimation of models between latent classes and
external variables. Psychometrika,
83, 871-892.
20. Kuha, J., Katsikatsou, M., and Moustaki, I. (2018). Latent variable modelling with non-ignorable item nonresponse:
Multigroup response propensity models for cross-national analysis. Journal of the Royal Statistical Society,
Series A, 181, 1169-1192.
21. Sturgis, P., Kuha, J. Baker, N., Callegaro,
M., Fisher, S., Green, J., Jennings, W., Lauderdale, B., and Smith, P. (2018). An assessment of the causes of the errors in the 2015 UK
General Election opinion polls. Journal
of the Royal Statistical Society, Series A, 181, 757-781.
·
Supplementary materials
for the paper (including example data and code) can be downloaded from here.
·
See also the related Sturgis
et al. (2016): Report
of the Inquiry into the 2015 British General Election Opinion Polls.
22. Kuha, J., Butt, S., Katsikatsou, M., and Skinner, C. J. (2018). The effect of probing "Don't Know" responses on
measurement quality and nonresponse in surveys. Journal of the American Statistical Association, 113, 26-40.
23. Wilson, B. and Kuha, J. (2018). Residential segregation and the fertility of immigrants and
their descendants. Population, Space
and Place, 24, e2098.
24. Ding, Y. Y., Kuha, J., and Murphy, M. (2017). Pathways from physical frailty to activity limitation in older
people: Identifying moderators and mediators in the English Longitudinal Study
of Ageing. Experimental Gerontology,
98, 169-176.
25. Bukodi, E., Goldthorpe, J. H. and Kuha, J. (2017). The pattern of social
fluidity within the British class structure: A topological model. Journal of the Royal Statistical Society,
Series A, 180, 841-862.
26. Ding, Y. Y., Kuha, J., and Murphy, M. (2017). Multidimensional
predictors of physical frailty in older people: Identifying how and for whom
they exert their effects. Biogerontology,
18, 237-252.
27. Reader, T. W., Mearns, K., Lopes, C., and Kuha. J. (2017). Organizational support
for workforce health and employee safety citizenship behaviors: A social
exchange relationship. Human
Relations, 70, 362-385.
28. Kuha, J. and Moustaki, I. (2015). Non-equivalence of
measurement in latent variable modeling of multigroup data: A sensitivity
analysis. Psychological Methods,
20, 523-536.
29. Hafez, M. S., Moustaki, I., and Kuha, J.
(2015). Analysis of
multivariate longitudinal data subject to nonrandom dropout. Structural Equation Modeling, 22,
193-201.
30. Bukodi, E., Goldthorpe, J. H., Waller, L., and Kuha, J. (2015). The mobility problem in
Britain: New findings from the analysis of birth cohort data. British Journal of Sociology, 66,
93-117.
31. Jackson, J. and Kuha, J. (2014). Worry about crime in a
cross-national context: A model-supported method of measurement using the
European Social Survey Data. Survey
Research Methods, 8, 109-126.
32. Sturgis, P.,
Brunton-Smith, I., Jackson, J., and Kuha, J. (2014). Ethnic diversity,
segregation, and the social cohesion of neighbourhoods in London. Ethnic and Racial Studies, 37,
1286-1309.
33. Kuha, J. and Jackson, J. (2014). The item count method for
sensitive survey questions: Modelling criminal behavior. Journal of the Royal
Statistical Society, Series C (Applied Statistics), 63, 321-341.
34. Skrondal, A. and Kuha, J. (2012). Improved regression
calibration. Psychometrika, 77,
649-669.
35. Jackson, J., Bradford, B., Hough, M., Kuha, J., Stares, S., Widdop, S.,
Fitzgerald, R., Yordanova, M., and Galev, T. (2011). Developing European
indicators of trust in justice. European
Journal of Criminology, 8, 267-285.
36. Curtice, J., Fisher, S. D., and Kuha, J. (2011). Confounding the
commentators: How the 2010 exit poll got it (more or less) right. Journal
of Elections, Public Opinion & Parties, 21, 211-235.
37. Kuha, J. and Firth, D. (2011). On the index of dissimilarity for lack of fit in loglinear and
log-multiplicative models. Computational
Statistics and Data Analysis, 55, 375-388.
38. Kuha, J. and Goldthorpe, J. H. (2010). Path analysis for
discrete variables: The role of education in social mobility. Journal of the Royal Statistical Society,
Series A, 173, 351-369.
39. Akritas, M. G., Antoniou, E. S., and Kuha, J. (2006). Nonparametric
analysis of factorial designs with random missingness: Bivariate data. Journal of the American Statistical
Association, 101, 1513-1526.
40. Kuha, J. (2004). AIC and BIC: comparisons of assumptions and performance. Sociological
Methods & Research, 33, 188-229. (See also publisher's errata for the
print edition of the paper, in SMR, 33, 417 (2005).)
41. Kuha, J. and Temple, J. (2003). Covariate measurement error in quadratic regression. International
Statistical Review, 71, 131-150.
42. Akritas, M. G., Kuha, J. and Osgood, D. W. (2002). A nonparametric approach
to matched pairs with missing data. Sociological Methods & Research,
30, 425-454.
43. Kuha, J., Skinner, C., and Palmgren, J. (1998). Misclassification error. In P. Armitage and T. Colton
(Eds.), Encyclopedia of Biostatistics, volume 4, pp. 2615-2621. New
York: Wiley. Reprinted in M. Gail and J. Benichou
(Eds.), Encyclopedia of Epidemiologic
Methods, 2000. New York: Wiley.
44. Kuha, J. (1997). Estimation by data augmentation in regression models with
continuous and discrete covariates measured with error. Statistics in
Medicine, 16, 189-202.
45. Kuha, J. and Skinner, C. (1997). Categorical data
analysis and misclassification. In L. Lyberg, P. Biemer, M. Collins, E. De
Leeuw, C. Dippo, N. Schwarz, and D. Trewin (eds.), Survey
Measurement and Process Quality, pp. 633-670. New York: Wiley.
46. Riihimäki, H., Viikari-Juntura, E., Moneta, G., Kuha, J., Videman, T., and
Tola, S. (1994). Incidence of sciatic pain among men in machine operating,
dynamic physical work, and sedentary work: A three-year follow-up. Spine,
19, 138-142.
47. Kuha, J. (1994). Corrections for exposure measurement error in logistic
regression models with an application to nutritional data. Statistics in
Medicine, 13, 1135-1148.
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edited: 1 November 2024]