Rachael A Hughes
Biographic Data
| ID | 7693519 |
|---|---|
| NAME | Rachael A Hughes |
| GIVEN NAMES | Rachael A |
| FAMILY NAME | Hughes |
| SIGNATURE | HUGHES R A |
| AFFILIATIONS | University of Bristol |
| ORCID | 0000-0003-0766-1410 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2008 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Time-sensitive testing pressures and Covid-19 outcomes
The association between SEP and SARS-CoV-2 testing changed over time, highlighting the potential of time-specific selection pressures to bias analyses of COVID-19. Positive and negative control analyses suggest that changes in the association between SEP and SARS-CoV-2 infection over time likely reflect true increases in socioeconomic inequalities
The proportion of missing data should not be used to guide decisions on multiple imputation
OBJECTIVES: Researchers are concerned whether multiple imputation (MI) or complete case analysis should be used when a large proportion of data are missing. We aimed to provide guidance for drawing conclusions from data with a large proportion of missingness. STUDY DESIGN AND SETTING: Via simulations, we investigated how the proportion of missing data, the fraction of missing information (FMI), and availability of auxiliary variables affected MI …
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…
Interventions to support shared decision making for hypertension
Determinants of global quality of life before and after major cancer surgery
An informal school-based peer-led intervention for smoking prevention in adolescence (Assist)
No prominent works on this page.
An informal school-based peer-led intervention for smoking prevention in adolescence (Assist)
Determinants of global quality of life before and after major cancer surgery
Interventions to support shared decision making for hypertension
The proportion of missing data should not be used to guide decisions on multiple imputation
OBJECTIVES: Researchers are concerned whether multiple imputation (MI) or complete case analysis should be used when a large proportion of data are missing. We aimed to provide guidance for drawing conclusions from data with a large proportion of missingness. STUDY DESIGN AND SETTING: Via simulations, we investigated how the proportion of missing data, the fraction of missing information (FMI), and availability of auxiliary variables affected MI …
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…
Time-sensitive testing pressures and Covid-19 outcomes
The association between SEP and SARS-CoV-2 testing changed over time, highlighting the potential of time-specific selection pressures to bias analyses of COVID-19. Positive and negative control analyses suggest that changes in the association between SEP and SARS-CoV-2 infection over time likely reflect true increases in socioeconomic inequalities
Medicine (4 works) · Advanced Causal Inference Techniques (2 works) · Computer Science (2 works) · Data mining (2 works) · Demography (2 works) · Econometrics (2 works) · Imputation (statistics) (2 works) · Internal Medicine (2 works) · Logistic regression (2 works) · Mathematics (2 works)