Table 1 A list .... (as shown in text).
From: Statistical challenges in haematopoietic cell transplantation
1. Fraser R. Inappropriate use of statistical power. (in press). |
2. De Wreede LC, Scheteling J, Putter H. Analysis of survival outcomes in haematopoietic cell transplant studies: pitfalls and solutions. (in press). |
3. Othus M, Zhang MJ, Gale RP. Clinical trials: design, endpoints and interpretation of outcomes. Bone Marrow Transplant. 2022;7:1–5. |
4. Cai J, Kim S. Case-cohort design in hematopoietic cell transplant studies. Bone Marrow Transplant. 2021;16:1–5. |
5. Hu ZH, Wang HL, Gale RP, Zhang MJ. A SAS macro for estimating direct adjusted survival functions for time-to-event data with or without left truncation. Bone Marrow Transplant. 2021;19:1–5. |
6. Moodie EE, Krakow EF. Precision medicine: Statistical methods for estimating adaptive treatment strategies. Bone Marrow Transplant. 2020;55:1890–6. |
7. Othus M, Gale RP, Hourigan CS, Walter RB. Statistics and measurable residual disease (MRD) testing: uses and abuses in hematopoietic cell transplantation. Bone Marrow Transplant. 2020;55:843–50. |
8. Gauthier J, Wu QV, Gooley TA. Cubic splines to model relationships between continuous variables and outcomes: a guide for clinicians. Bone Marrow Transplant. 2020;55:675–80. |
9. Hu ZH, Gale RP, Zhang MJ. Direct adjusted survival and cumulative incidence curves for observational studies. Bone Marrow Transplant. 2020;55:538–43. |
10. Zheng C, Dai R, Gale RP, Zhang MJ. Causal inference in randomized clinical trials. Bone Marrow Transplant. 2020;55:4–8. |
11. Gale RP, Zhang MJ. Statistical analyses of clinical trials in haematopoietic cell transplantation or why there is a strong correlation between people drowning after falling out of a fishing boat and marriage rate in Kentucky. Bone Marrow Transplant. 2020;55:1–3. |
