Jonathan A C Sterne
Biographic Data
| ID | 1735605 |
|---|---|
| NAME | Jonathan A C Sterne |
| GIVEN NAMES | Jonathan A C |
| FAMILY NAME | Sterne |
| SIGNATURE | STERNE J A C |
| AFFILIATIONS | From the University of Bristol, Bristol, United Kingdom; Kleijnen Systematic Reviews, York, United Kingdom; University of Oxford, Oxford, United Kingdom; University of Birmingham, Birmingham, United Kingdom; University Medical Center Utrecht, Utrecht the Netherlands; University of Amsterdam, Amsterdam, the Netherlands; and University of Bern, Bern, Switzerland. |
| VERIFIED | No |
| TOTAL WORKS | 9 |
| TOTAL CITATIONS | 90 |
| WORKS AS AUTHOR | 9 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2000 |
| LATEST PUBLICATION YEAR | 2019 |
| H-INDEX | 4 |
Accounting for missing data in statistical analyses
BACKGROUND: Missing data are unavoidable in epidemiological research, potentially leading to bias and loss of precision. Multiple imputation (MI) is widely advocated as an improvement over complete case analysis (CCA). However, contrary to widespread belief, CCA is preferable to MI in some situations. METHODS: We provide guidance on choice of analysis when data are incomplete. Using causal diagrams to depict missingness mechanisms, we describe wh…
Quadas-2
In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Sig…
Was the economic crisis 1997-1998 responsible for rising suicide rates in East/Southeast Asia? A time-trend analysis for Japan, Hong Kong, South Korea, Taiwan, Singapore and Thailand
Mendelian randomization
Observational epidemiological studies suffer from many potential biases, from confounding and from reverse causation, and this limits their ability to robustly identify causal associations. Several high‐profile situations exist in which randomized controlled trials of precisely the same intervention that has been examined in observational studies have produced markedly different findings. In other observational sciences, the use of instrumental v…
Combining individual and ecological data to determine compositional and contextual socio-economic risk factors for suicide
The geography of despair among 15–44-year-old men in England and Wales
Objective: To investigate the spatial patterning and possible contributors to the geographical distribution of suicide among 15–44- year-old men. Design: Small-area analysis and mapping of geo-coded 1988–94 suicide mortality data and 1991 census data using random-effects smoothing. Setting: 9265 electoral wards in England and Wales (mean population of men aged 15–44- years: about 1220). Main results: Two main patterns emerged: (a) in all of the 1…
Frequent job change and associated health
Funnel plots for detecting bias in meta-analysis
Publication and related bias in meta-analysis
Was the economic crisis 1997-1998 responsible for rising suicide rates in East/Southeast Asia? A time-trend analysis for Japan, Hong Kong, South Korea, Taiwan, Singapore and Thailand
Combining individual and ecological data to determine compositional and contextual socio-economic risk factors for suicide
The geography of despair among 15–44-year-old men in England and Wales
Objective: To investigate the spatial patterning and possible contributors to the geographical distribution of suicide among 15–44- year-old men. Design: Small-area analysis and mapping of geo-coded 1988–94 suicide mortality data and 1991 census data using random-effects smoothing. Setting: 9265 electoral wards in England and Wales (mean population of men aged 15–44- years: about 1220). Main results: Two main patterns emerged: (a) in all of the 1…
Frequent job change and associated health
Publication and related bias in meta-analysis
Funnel plots for detecting bias in meta-analysis
Frequent job change and associated health
The geography of despair among 15–44-year-old men in England and Wales
Objective: To investigate the spatial patterning and possible contributors to the geographical distribution of suicide among 15–44- year-old men. Design: Small-area analysis and mapping of geo-coded 1988–94 suicide mortality data and 1991 census data using random-effects smoothing. Setting: 9265 electoral wards in England and Wales (mean population of men aged 15–44- years: about 1220). Main results: Two main patterns emerged: (a) in all of the 1…
Combining individual and ecological data to determine compositional and contextual socio-economic risk factors for suicide
Mendelian randomization
Observational epidemiological studies suffer from many potential biases, from confounding and from reverse causation, and this limits their ability to robustly identify causal associations. Several high‐profile situations exist in which randomized controlled trials of precisely the same intervention that has been examined in observational studies have produced markedly different findings. In other observational sciences, the use of instrumental v…
Was the economic crisis 1997-1998 responsible for rising suicide rates in East/Southeast Asia? A time-trend analysis for Japan, Hong Kong, South Korea, Taiwan, Singapore and Thailand
Quadas-2
In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Sig…
Accounting for missing data in statistical analyses
BACKGROUND: Missing data are unavoidable in epidemiological research, potentially leading to bias and loss of precision. Multiple imputation (MI) is widely advocated as an improvement over complete case analysis (CCA). However, contrary to widespread belief, CCA is preferable to MI in some situations. METHODS: We provide guidance on choice of analysis when data are incomplete. Using causal diagrams to depict missingness mechanisms, we describe wh…
Medicine (7 works) · Demography (4 works) · Health disparities and outcomes (4 works) · Mathematics (4 works) · Demography (3 works) · Econometrics (3 works) · Environmental health (3 works) · Geography (3 works) · Meta-analysis and systematic reviews (3 works) · Population (3 works)