BarthelF. M.-S., and RoystonP.2006. Graphical representation of interactions. Stata Journal6: 348–363.
2.
BarthelF. M.-S., and RoystonP.2008. Software Updates: Graphical representation of interactions. Stata Journal8: 594.
3.
BarthelF. M.-S., RoystonP., and BabikerA.2005. A menu-driven facility for complex sample size calculation in randomized controlled trials with a survival or a binary outcome: Update. Stata Journal5: 123–129.
4.
BarthelF. M.-S., RoystonP., and ParmarM. K. B.2009. A menu-driven facility for sample-size calculation in novel multiarm, multistage randomized controlled trials with a time-to-event outcome. Stata Journal9: 505–523.
5.
BrattonD. J., Choodari-OskooeiB., and RoystonP.2015. A menu-driven facility for sample-size calculation in multiarm, multistage randomized controlled trials with time-to-event outcomes: Update. Stata Journal15: 350–368.
6.
CarlinJ. B., GalatiJ. C., and RoystonP.2008. A new framework for managing and analyzing multiply imputed data in Stata. Stata Journal8: 49–67.
7.
HosmerD. W.2009. Book reviews: Multivariable Model-building: A Pragmatic Approach to Regression Analysis Based on Fractional Polynomials for Modelling Continuous Variables by Royston, P. and Sauerbrei, W. Biometrics65: 989–990.
8.
HosmerD. W., and RoystonP.2002. Using Aalen's linear hazards model to investigate time-varying effects in the proportional hazards regression model. Stata Journal2: 331–350.
9.
LambertP. C., and RoystonP.2009. Further development of flexible parametric models for survival analysis. Stata Journal9: 265–290.
10.
NewtonH. J., and CoxN. J.2012. Announcement of the Stata Journal Editors’ Prize 2012. Stata Journal12: 1–2.
11.
RoystonP.1991a. gr6: Lowess smoothing. Stata Technical Bulletin3: 7–9. Reprinted in Stata Technical Bulletin Reprints, vol. 1, pp. 41–44. College Station, TX: Stata Press.
12.
RoystonP.1991b. sg3.1: Tests for departure from normality. Stata Technical Bulletin2: 16–17. Reprinted in Stata Technical Bulletin Reprints, vol. 1, pp. 101–104. College Station, TX: Stata Press.
13.
RoystonP.1991c. sg3.2: Shapiro–Wilk and Shapiro–Francia tests. Stata Technical Bulletin3: 19. Reprinted in Stata Technical Bulletin Reprints, vol. 1, p. 105. College Station, TX: Stata Press.
14.
RoystonP.1991d. sg3.5: Comment on sg3.4 and an improved D'Agostino test. Stata Technical Bulletin3: 23–24. Reprinted in Stata Technical Bulletin Reprints, vol. 1, pp. 110–112. College Station, TX: Stata Press.
15.
RoystonP.1991e. sg3.6: A response to sg3.3: Comment on tests of normality. Stata Technical Bulletin4: 8–9. Reprinted in Stata Technical Bulletin Reprints, vol. 1, pp. 112–114. College Station, TX: Stata Press.
16.
RoystonP.1992a. srd10: Maximum-likelihood estimation for Box–Cox power transformation. Stata Technical Bulletin5: 25–26. Reprinted in Stata Technical Bulletin Reprints, vol. 1, pp. 188–190. College Station, TX: Stata Press.
17.
RoystonP.1992b. sg1.2: Nonlinear regression command. Stata Technical Bulletin7: 11–18. Reprinted in Stata Technical Bulletin Reprints, vol. 2, pp. 112–120. College Station, TX: Stata Press.
18.
RoystonP.1992c. sg1.3: Nonlinear regression command, bug fix. Stata Technical Bulletin18: 12. Reprinted in Stata Technical Bulletin Reprints, vol. 2, p. 120. College Station, TX: Stata Press.
19.
RoystonP.1992d. sg7: Centile estimation command. Stata Technical Bulletin18: 12–15. Reprinted in Stata Technical Bulletin Reprints, vol. 2, pp. 122–125. College Station, TX: Stata Press.
20.
RoystonP.1993a. sg1.4: Standard nonlinear curve fits. Stata Technical Bulletin11: 17. Reprinted in Stata Technical Bulletin Reprints, vol. 2, p. 121. College Station, TX: Stata Press.
21.
RoystonP.1993b. sg1.5: Standard nonlinear curve fits update. Stata Technical Bulletin12: 14. Reprinted in Stata Technical Bulletin Reprints, vol. 2, pp. 121–122. College Station, TX: Stata Press.
22.
RoystonP.1993c. sqv7: Cusum plots and tests for binary variables. Stata Technical Bulletin12: 16–17. Reprinted in Stata Technical Bulletin Reprints, vol. 2, pp. 175–177. College Station, TX: Stata Press.
23.
RoystonP.1994a. sg22: Generalized linear models: Revision of glm. Stata Technical Bulletin18: 6–11. Reprinted in Stata Technical Bulletin Reprints, vol. 3, pp. 112–121. College Station, TX: Stata Press.
24.
RoystonP.1994b. sg22.3: Generalized linear models: Revision of glm. Rejoinder. Stata Technical Bulletin19: 17. Reprinted in Stata Technical Bulletin Reprints, vol. 3, p. 126. College Station, TX: Stata Press.
25.
RoystonP.1995a. ip8: An enhanced for command. Stata Technical Bulletin26: 12. Reprinted in Stata Technical Bulletin Reprints, vol. 5, p. 65. College Station, TX: Stata Press.
26.
RoystonP.1995b. sg26.3: Fractional polynomial utilities. Stata Technical Bulletin25: 9–13. Reprinted in Stata Technical Bulletin Reprints, vol. 5, pp. 82–87. College Station, TX: Stata Press.
27.
RoystonP.1996a. ip8.1: An even more enhanced for command. Stata Technical Bulletin30: 5–6. Reprinted in Stata Technical Bulletin Reprints, vol. 5, pp. 65–66. College Station, TX: Stata Press.
28.
RoystonP.1996b. ip9: Repeat Stata command by variable(s). Stata Technical Bulletin27: 3–5. Reprinted in Stata Technical Bulletin Reprints, vol. 5, pp. 67–69. College Station, TX: Stata Press.
29.
RoystonP.1996c. sg47: A plot and a test for the χ2 distribution. Stata Technical Bulletin29: 26–27. Reprinted in Stata Technical Bulletin Reprints, vol. 5, pp. 142–144. College Station, TX: Stata Press.
30.
RoystonP.1996d. gr21: Flexible axis scaling. Stata Technical Bulletin34: 9–10. Reprinted in Stata Technical Bulletin Reprints, vol. 6, pp. 34–36. College Station, TX: Stata Press.
31.
RoystonP.1998. sg82: Fractional polynomials for st data. Stata Technical Bulletin43: 32. Reprinted in Stata Technical Bulletin Reprints, vol. 8, p. 133. College Station, TX: Stata Press.
32.
RoystonP.2000. ip9.1: Update of the byvar command. Stata Technical Bulletin55: 2. Reprinted in Stata Technical Bulletin Reprints, vol. 10, p. 69. College Station, TX: Stata Press.
33.
RoystonP.2001a. Flexible parametric alternatives to the Cox model, and more. Stata Journal1: 1–28.
34.
RoystonP.2001b. Sort a list of items. Stata Journal1: 105–106.
35.
RoystonP.2002. Software Updates: Flexible parametric alternatives to the Cox model, and more. Stata Journal2: 226.
36.
RoystonP.2004a. Flexible parametric alternatives to the Cox model: Update. Stata Journal4: 98–101.
37.
RoystonP.2004b. Multiple imputation of missing values. Stata Journal4: 227–241.
38.
RoystonP.2004c. Stata tip 11: The nolog option with maximum-likelihood modeling commands. Stata Journal4: 356.
39.
RoystonP.2004d. Stata tip 7: Copying and pasting under Windows. Stata Journal4: 220.
40.
RoystonP.2005a. Multiple imputation of missing values: Update. Stata Journal5: 188–201.
41.
RoystonP.2005b. Multiple imputation of missing values: Update of ice. Stata Journal5: 527–536.
42.
RoystonP.2005c. Stata at 20: A personal view. Stata Journal5: 43–45.
43.
RoystonP.2005d. Stata tip 19: A way to leaner, faster graphs. Stata Journal5: 279.
44.
RoystonP.2006. Explained variation for survival models. Stata Journal6: 83–96.
45.
RoystonP.2007a. Multiple imputation of missing values: Further update of ice, with an emphasis on interval censoring. Stata Journal7: 445–464.
46.
RoystonP.2007b. Profile likelihood for estimation and confidence intervals. Stata Journal7: 376–387.
47.
RoystonP.2009. Multiple imputation of missing values: Further update of ice, with an emphasis on categorical variables. Stata Journal9: 466–477.
48.
RoystonP.2012. Tools to simulate realistic censored survival-time distributions. Stata Journal12: 639–654.
49.
RoystonP.2013a. cmpute: A tool to generate or replace a variable. Stata Journal13: 862–866.
50.
RoystonP.2013b. marginscontplot: Plotting the marginal effects of continuous predictors. Stata Journal13: 510–527.
51.
RoystonP.2014a. A smooth covariate rank transformation for use in regression models with a sigmoid dose–reponse function. Stata Journal14: 329–341.
52.
RoystonP.2014b. Software Updates: A smooth covariate rank transformation for use in regression models with a sigmoid dose–reponse function. Stata Journal14: 997.
53.
RoystonP.2014c. Software Updates: Tools to simulate realistic censored survival-time distributions. Stata Journal14: 451.
54.
RoystonP.2014d. Tools for checking calibration of a Cox model in external validation: Approach based on individual event probabilities. Stata Journal14: 738–755.
55.
RoystonP.2015a. Estimating the treatment effect in a clinical trial using difference in restricted mean survival time. Stata Journal15: 1098–1117.
56.
RoystonP.2015b. Tools for checking calibration of a Cox model in external validation: Prediction of population-averaged survival curves based on risk groups. Stata Journal15: 275–291.
57.
RoystonP., and AltmanD. G.1994a. sg26: Using fractional polynomials to model curved regression relationships. Stata Technical Bulletin21: 11–23. Reprinted in Stata Technical Bulletin Reprints, vol. 4, pp. 110–128. College Station, TX: Stata Press.
58.
RoystonP., and AltmanD. G.1994b. sg26.1: Fractional polynomials: Correction. Stata Technical Bulletin22: 11–12. Reprinted in Stata Technical Bulletin Reprints, vol. 4, p. 128. College Station, TX: Stata Press.
59.
RoystonP., and AmblerG.1998a. sg79: Generalized additive models. Stata Technical Bulletin42: 38–43. Reprinted in Stata Technical Bulletin Reprints, vol. 7, pp. 217–224. College Station, TX: Stata Press.
60.
RoystonP., and AmblerG.1998b. sg81: Multivariable fractional polynomials. Stata Technical Bulletin43: 24–32. Reprinted in Stata Technical Bulletin Reprints, vol. 8, pp. 123–132. College Station, TX: Stata Press.
61.
RoystonP., and AmblerG.1999a. sg112: Nonlinear regression models involving power or exponential functions of covariates. Stata Technical Bulletin49: 25–30. Reprinted in Stata Technical Bulletin Reprints, vol. 9, pp. 173–179. College Station, TX: Stata Press.
62.
RoystonP., and AmblerG.1999b. sg112.1: Nonlinear regression models involving power or exponential functions of covariates: Update. Stata Technical Bulletin50: 26. Reprinted in Stata Technical Bulletin Reprints, vol. 9, p. 180. College Station, TX: Stata Press.
63.
RoystonP., and AmblerG.1999c. sg81.1: Multivariable fractional polynomials: Update. Stata Technical Bulletin49: 17–23. Reprinted in Stata Technical Bulletin Reprints, vol. 9, pp. 161–168. College Station, TX: Stata Press.
64.
RoystonP., and AmblerG.1999d. sg81.2: Multivariable fractional polynomials: Update. Stata Technical Bulletin50: 25. Reprinted in Stata Technical Bulletin Reprints, vol. 9, p. 168. College Station, TX: Stata Press.
65.
RoystonP., and BabikerA.2002. A menu-driven facility for complex sample size calculation in randomized controlled trials with a survival or a binary outcome. Stata Journal2: 151–163.
66.
RoystonP., and BarthelF. M.-S.2010. Projection of power and events in clinical trials with a time-to-event outcome. Stata Journal10: 386–394.
67.
RoystonP., CarlinJ. B., and WhiteI. R.2009. Multiple imputation of missing values: New features for mim. Stata Journal9: 252–264.
68.
RoystonP., and CoxN. J.2005. A multivariable scatterplot smoother. Stata Journal5: 405–412.
69.
RoystonP., and GoldsteinR.1993. sg18: An improved R2. Stata Technical Bulletin14: 19–22. Reprinted in Stata Technical Bulletin Reprints, vol. 3, pp. 94–98. College Station, TX: Stata Press.
70.
RoystonP., and GouldW.1993. os8: Stata and Lotus 123. Stata Technical Bulletin13: 14–17. Reprinted in Stata Technical Bulletin Reprints, vol. 3, pp. 63–66. College Station, TX: Stata Press.
71.
RoystonP., and LambertP. C.2011. Flexible Parametric Survival Analysis Using Stata: Beyond the Cox Model.College Station, TX: Stata Press.
72.
RoystonP., and SasieniP.1994. dm16: Compact listing of a single variable. Stata Technical Bulletin17: 7–8. Reprinted in Stata Technical Bulletin Reprints, vol. 3, pp. 41–43. College Station, TX: Stata Press.
73.
RoystonP., and SauerbreiW.2007. Multivariable modeling with cubic regression splines: A principled approach. Stata Journal7: 45–70.
74.
RoystonP., and SauerbreiW.2008. Multivariable Model-building: A Pragmatic Approach to Regression Analysis Based on Fractional Polynomials for Modelling Continuous Variables.Chichester, UK: Wiley.
75.
RoystonP., and SauerbreiW.2009a. Bootstrap assessment of the stability of multivariable models. Stata Journal9: 547–570.
76.
RoystonP., and SauerbreiW.2009b. Two techniques for investigating interactions between treatment and continuous covariates in clinical trials. Stata Journal9: 230–251.
77.
RoystonP., and SauerbreiW.2016. mfpa: Extension of mfp using the ACD covariate transformation for enhanced parametric multivariable modeling. Stata Journal16: 72–87.
78.
SasieniP., and RoystonP.1994. gr14: dotplot: Comparative scatterplots. Stata Technical Bulletin19: 8–10. Reprinted in Stata Technical Bulletin Reprints, vol. 4, pp. 50–54. College Station, TX: Stata Press.
79.
SasieniP., and RoystonP.1998. sed9.1: Pointwise confidence intervals for running. Stata Technical Bulletin41: 17–23. Reprinted in Stata Technical Bulletin Reprints, vol. 7, pp. 156–163. College Station, TX: Stata Press.
80.
SasieniP., RoystonP., and CoxN. J.2005. Symmetric nearest neighbor linear smoothers. Stata Journal5: 285.
81.
WrightE., and RoystonP.1996. sbe13: Age-specific reference intervals (“normal ranges”). Stata Technical Bulletin34: 24–34. Reprinted in Stata Technical Bulletin Reprints, vol. 6, pp. 91–104. College Station, TX: Stata Press.
82.
WrightE., and RoystonP.1997a. sbe13.1: Correction to age-specific reference intervals (“normal ranges”). Stata Technical Bulletin35: 21. Reprinted in Stata Technical Bulletin Reprints, vol. 6, p. 104. College Station, TX: Stata Press.
83.
WrightE., and RoystonP.1997b. sbe13.2: Correction to age-specific reference intervals (“normal ranges”). Stata Technical Bulletin36: 15. Reprinted in Stata Technical Bulletin Reprints, vol. 6, p. 104. College Station, TX: Stata Press.
84.
WrightE., and RoystonP.1997c. sbe13.3: Correction to age-specific reference intervals (“normal ranges”). Stata Technical Bulletin40: 16. Reprinted in Stata Technical Bulletin Reprints, vol. 7, p. 93. College Station, TX: Stata Press.
85.
WrightE., and RoystonP.1997d. sbe15: Age-specific reference intervals for normally distributed data. Stata Technical Bulletin38: 4–9. Reprinted in Stata Technical Bulletin Reprints, vol. 7, pp. 93–100. College Station, TX: Stata Press.
86.
WrightE., and RoystonP.1999. sbe25: Two methods for assessing the goodness-of-fit of age-specific reference intervals. Stata Technical Bulletin47: 8–15. Reprinted in Stata Technical Bulletin Reprints, vol. 8, pp. 100–108. College Station, TX: Stata Press.