| What happens when econometrics and psychometrics collide? An example using the PISA data J Jerrim, LA Lopez-Agudo, OD Marcenaro-Gutierrez, N Shure Economics of Education Review 61, 51-58, 2017 | 145 | 2017 |
| Adolescents’ physical activity: cross-national comparisons of levels, distributions and disparities across 52 countries D Bann, S Scholes, M Fluharty, N Shure International Journal of Behavioral Nutrition and Physical Activity 16, 1-11, 2019 | 90 | 2019 |
| Achievement of 15-Year-Olds in Wales: PISA 2015 National Report N Shure, J Jerrim Department for Education, 2016 | 62 | 2016 |
| Moving on up:‘first in family’university graduates in England M Henderson, N Shure, A Adamecz-Völgyi Oxford Review of Education 46 (6), 734-751, 2020 | 41 | 2020 |
| Is Canada really an education superpower? The impact of non-participation on results from PISA 2015 J Anders, S Has, J Jerrim, N Shure, L Zieger Educational Assessment, Evaluation and Accountability 33, 229-249, 2021 | 34 | 2021 |
| How robust are cross‐country comparisons of PISA scores to the scaling model used? J Jerrim, P Parker, A Choi, AK Chmielewski, C Sälzer, N Shure Educational Measurement: Issues and Practice 37 (4), 28-39, 2018 | 27 | 2018 |
| Is ‘first in family’a good indicator for widening university participation? A Adamecz-Völgyi, M Henderson, N Shure Economics of Education Review 78, 102038, 2020 | 24 | 2020 |
| Children in jobless households across Europe: evidence on the association with medium-and long-term outcomes L Macmillan, P Gregg, J Jerrim, N Shure Journal of Poverty and Social Justice 26 (3), 335-358, 2018 | 24 | 2018 |
| Non-cognitive peer effects in secondary education N Shure Labour Economics 73, 102074, 2021 | 23 | 2021 |
| An information distortion model of social class differences in math self-concept, intrinsic value, and utility value. PD Parker, HW Marsh, J Guo, J Anders, N Shure, T Dicke Journal of Educational Psychology 110 (3), 445, 2018 | 23 | 2018 |
| Achievement of 15-Year Olds in Wales: PISA 2015 National Report J Jerrim, N Shure London: UCL Institute of Education, 2016 | 18 | 2016 |
| Conditioning: how background variables can influence PISA scores LR Zieger, J Jerrim, J Anders, N Shure Assessment in Education: Principles, Policy & Practice 29 (6), 632-652, 2022 | 13 | 2022 |
| School hours and maternal labor supply N Shure Kyklos 72 (1), 118-151, 2019 | 13 | 2019 |
| The labor market returns to “first-in-family” university graduates A Adamecz-Völgyi, M Henderson, N Shure Journal of Population Economics 36 (3), 1395-1429, 2023 | 12 | 2023 |
| Does school average achievement explain the effect of socioeconomic status on math and reading interest? A test of the Information Distortion Model P Parker, T Sanders, J Anders, B Sahdra, N Shure, J Jerrim, N Cull Learning and Instruction 73, 101432, 2021 | 10 | 2021 |
| To weight or not to weight?: the case of PISA data LA Lopez-Agudo, J Jerrim, ODM Gutierrez, N Shure Investigaciones de Economía de la Educación volume 12 12, 285-302, 2017 | 9 | 2017 |
| The gender gap in top jobs–the role of overconfidence A Adamecz-Völgyi, N Shure Labour Economics 79, 102283, 2022 | 8 | 2022 |
| Does academic self-concept predict further and higher education participation? M Henderson, K Hansen, N Shure Centre for Global Higher Education, 2017 | 7 | 2017 |
| Is Canada really an education superpower? The impact of exclusions and non-response on results from PISA 2015 J Anders, S Has, J Jerrim, N Shure, L Zieger UC L Institute of Education. Working Paper, 2019 | 5 | 2019 |
| The role of academic self-concept in post-compulsory achievement, transitions and labour market outcomes K Hansen, M Henderson, N Shure Cambridge Journal of Education 53 (3), 293-309, 2023 | 4 | 2023 |
