메뉴 건너뛰기




Volumn 79, Issue 1, 2015, Pages 132-147

Covariate selection in pharmacometric analyses: A review of methods

Author keywords

all subset regression; lasso; stepwise procedures; variable selection

Indexed keywords

ARTICLE; BAYES THEOREM; COVARIATE SELECTION; DRUG DOSE; GENETIC ALGORITHM; MAXIMUM LIKELIHOOD METHOD; NESTING; PHARMACOLOGY; PHARMACOMETRIC ANALYSIS; PREDICTOR VARIABLE; STATISTICAL ANALYSIS; ALGORITHM; BIOLOGICAL MODEL; COMPUTER SIMULATION; HUMAN; PHARMACOKINETICS; REGRESSION ANALYSIS;

EID: 85000154671     PISSN: 03065251     EISSN: 13652125     Source Type: Journal    
DOI: 10.1111/bcp.12451     Document Type: Article
Times cited : (61)

References (63)
  • 1
    • 77953753772 scopus 로고    scopus 로고
    • Performance of using multiple stepwise algorithms for variable selection
    • Wiegand RE,. Performance of using multiple stepwise algorithms for variable selection. Stat Med 2010; 29: 1647-1659.
    • (2010) Stat Med , vol.29 , pp. 1647-1659
    • Wiegand, R.E.1
  • 2
    • 0001878035 scopus 로고
    • Multiple regression analysis
    • eds Ralston A. Wilf H.S. New York: Wiley
    • Efroymson MA,. Multiple regression analysis. In: Mathematical Method for Digital Computers, eds, Ralston A, Wilf HS,. New York: Wiley, 1960; 191-203.
    • (1960) Mathematical Method for Digital Computers , pp. 191-203
    • Efroymson, M.A.1
  • 3
    • 84978599386 scopus 로고
    • On multiple regression analysis
    • Hamaker HC,. On multiple regression analysis. Stat Neerl 1962; 16: 31-56.
    • (1962) Stat Neerl , vol.16 , pp. 31-56
    • Hamaker, H.C.1
  • 4
    • 0019974098 scopus 로고
    • Interspecies scaling, allometry, physiological time, and the ground plan of pharmacokinetics
    • Boxenbaum H,. Interspecies scaling, allometry, physiological time, and the ground plan of pharmacokinetics. J Pharmacokinet Biopharm 1982; 10: 201-227.
    • (1982) J Pharmacokinet Biopharm , vol.10 , pp. 201-227
    • Boxenbaum, H.1
  • 5
    • 84942484786 scopus 로고
    • Ridge regression: Biased estimation for non-orthogonal problems
    • Hoerl AE, Kennard RW,. Ridge regression: biased estimation for non-orthogonal problems. Technometrics 1970a; 12: 55-67.
    • (1970) Technometrics , vol.12 , pp. 55-67
    • Hoerl, A.E.1    Kennard, R.W.2
  • 7
    • 0000957593 scopus 로고
    • Principal components regression in exploratory statistical research
    • Massy WF,. Principal components regression in exploratory statistical research. J Am Stat Assoc 1965; 560: 234-246.
    • (1965) J Am Stat Assoc , vol.560 , pp. 234-246
    • Massy, W.F.1
  • 9
    • 0028627727 scopus 로고
    • Comparison of the Akaike information criterion, the Schwarz criterion and the F test as guides to model selection
    • Ludden TM, Beal SL, Sheiner LB,. Comparison of the Akaike information criterion, the Schwarz criterion and the F test as guides to model selection. J Pharmacokinet Biopharm 1994; 29: 431-445.
    • (1994) J Pharmacokinet Biopharm , vol.29 , pp. 431-445
    • Ludden, T.M.1    Beal, S.L.2    Sheiner, L.B.3
  • 10
    • 0031506560 scopus 로고    scopus 로고
    • Bayesian model averaging for linear regression models
    • Raftery AE, Madigan D, Hoeting JA,. Bayesian model averaging for linear regression models. J Am Stat Assoc 1997; 92: 179-191.
    • (1997) J Am Stat Assoc , vol.92 , pp. 179-191
    • Raftery, A.E.1    Madigan, D.2    Hoeting, J.A.3
  • 11
    • 1142277415 scopus 로고    scopus 로고
    • Frequentist model average estimators
    • Hjort NL, Claeskens G,. Frequentist model average estimators. J Am Stat Assoc 2003; 98: 879-899.
    • (2003) J Am Stat Assoc , vol.98 , pp. 879-899
    • Hjort, N.L.1    Claeskens, G.2
  • 12
    • 0035863226 scopus 로고    scopus 로고
    • Design evaluation for a population pharmacokinetic study using clinical trial simulations: A case study
    • Kowalski KG, Hutmacher MM,. Design evaluation for a population pharmacokinetic study using clinical trial simulations: a case study. Stat Med 2001a; 20: 75-91.
    • (2001) Stat Med , vol.20 , pp. 75-91
    • Kowalski, K.G.1    Hutmacher, M.M.2
  • 13
    • 0028031207 scopus 로고
    • Interaction between structural, statistical, and covariate models in population pharmacokinetic analysis
    • Wade JR, Beal SL, Sambol NC,. Interaction between structural, statistical, and covariate models in population pharmacokinetic analysis. J Pharmacokinet Biopharm 1994; 22: 165-177.
    • (1994) J Pharmacokinet Biopharm , vol.22 , pp. 165-177
    • Wade, J.R.1    Beal, S.L.2    Sambol, N.C.3
  • 14
    • 0017280570 scopus 로고
    • The analysis and selection of variables in linear regression
    • Hocking RR,. The analysis and selection of variables in linear regression. Biometrics 1976; 32: 1-49.
    • (1976) Biometrics , vol.32 , pp. 1-49
    • Hocking, R.R.1
  • 16
    • 85004844353 scopus 로고
    • Backward, forward and stepwise automated subset selection algorithms: Frequency of obtaining authentic and noise variables
    • Derksen S, Keselman HJ,. Backward, forward and stepwise automated subset selection algorithms: frequency of obtaining authentic and noise variables. Br J Math Stat Psychol 1992; 45: 265-282.
    • (1992) Br J Math Stat Psychol , vol.45 , pp. 265-282
    • Derksen, S.1    Keselman, H.J.2
  • 17
    • 84942487147 scopus 로고
    • Ridge regression: Applications to non-orthogonal problems
    • Hoerl AE, Kennard RW,. Ridge regression: applications to non-orthogonal problems. Technometrics 1970b; 12: 69-82.
    • (1970) Technometrics , vol.12 , pp. 69-82
    • Hoerl, A.E.1    Kennard, R.W.2
  • 18
    • 33846430457 scopus 로고    scopus 로고
    • Modeling the exposure-response relationship of etanercept in the treatment of patients with chronic moderate to severe plaque psoriasis
    • Hutmacher MM, Nestorov I, Ludden T, Zitnik R, Banfield C,. Modeling the exposure-response relationship of etanercept in the treatment of patients with chronic moderate to severe plaque psoriasis. J Clin Pharmacol 2007; 47: 238-248.
    • (2007) J Clin Pharmacol , vol.47 , pp. 238-248
    • Hutmacher, M.M.1    Nestorov, I.2    Ludden, T.3    Zitnik, R.4    Banfield, C.5
  • 19
    • 0018115641 scopus 로고
    • Assessing the accuracy of the maximum likelihood estimator: Observed versus expected fisher information
    • Efron B, Hinkley DV,. Assessing the accuracy of the maximum likelihood estimator: observed versus expected fisher information. Biometrika 1978; 65: 457-487.
    • (1978) Biometrika , vol.65 , pp. 457-487
    • Efron, B.1    Hinkley, D.V.2
  • 20
    • 84988052077 scopus 로고
    • Nonparametric standard errors and confidence intervals
    • Efron B,. Nonparametric standard errors and confidence intervals. Can J Stat 1981; 9: 139-172.
    • (1981) Can J Stat , vol.9 , pp. 139-172
    • Efron, B.1
  • 21
    • 84905002632 scopus 로고
    • A note on screening regression equations
    • Freedman DA,. A note on screening regression equations. Am Stat 1983; 37: 152-155.
    • (1983) Am Stat , vol.37 , pp. 152-155
    • Freedman, D.A.1
  • 23
    • 0344761710 scopus 로고
    • Beal S.L. Sheiner L.B. Boeckmann A.J. eds. Ellicott City, USA: Icon Development Solutions
    • Beal SL, Sheiner LB, Boeckmann AJ, eds. NONMEM Users Guides. Ellicott City, USA: Icon Development Solutions, 1989-2006.
    • (1989) NONMEM Users Guides
  • 24
    • 0000474486 scopus 로고    scopus 로고
    • A note on the use of Laplace's approximation for nonlinear mixed-effects models
    • Vonesh EF,. A note on the use of Laplace's approximation for nonlinear mixed-effects models. Biometrika 1996; 83: 447-452.
    • (1996) Biometrika , vol.83 , pp. 447-452
    • Vonesh, E.F.1
  • 25
    • 0034954242 scopus 로고    scopus 로고
    • Assessment of actual significance levels for covariate effects in NONMEM
    • Wählby U, Jonsson EN, Karlsson MO,. Assessment of actual significance levels for covariate effects in NONMEM. J Pharmacokinet Pharmacodyn 2001; 28: 231-252.
    • (2001) J Pharmacokinet Pharmacodyn , vol.28 , pp. 231-252
    • Wählby, U.1    Jonsson, E.N.2    Karlsson, M.O.3
  • 26
    • 0036705010 scopus 로고    scopus 로고
    • Commentary on significance levels for covariate effects in NONMEM
    • discussion 411-412
    • Beal SL,. Commentary on significance levels for covariate effects in NONMEM. J Pharmacokinet Pharmacodyn 2002; 29: 403-410; discussion 411-412.
    • (2002) J Pharmacokinet Pharmacodyn , vol.29 , pp. 403-410
    • Beal, S.L.1
  • 27
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • Akaike H,. A new look at the statistical model identification. IEEE Trans Automatic Control 1974; 19: 716-723.
    • (1974) IEEE Trans Automatic Control , vol.19 , pp. 716-723
    • Akaike, H.1
  • 28
    • 70349119250 scopus 로고
    • Regression and time series model selection in small samples
    • Hurvich CM, Tsai CL,. Regression and time series model selection in small samples. Biometrika 1989; 76: 297-307.
    • (1989) Biometrika , vol.76 , pp. 297-307
    • Hurvich, C.M.1    Tsai, C.L.2
  • 29
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwarz G,. Estimating the dimension of a model. Ann Stat 1978; 6: 461-465.
    • (1978) Ann Stat , vol.6 , pp. 461-465
    • Schwarz, G.1
  • 30
    • 80054747535 scopus 로고    scopus 로고
    • Bayesian information criterion for longitudinal and clustered data
    • Jones RH,. Bayesian information criterion for longitudinal and clustered data. Stat Med 2011; 30: 3050-3056.
    • (2011) Stat Med , vol.30 , pp. 3050-3056
    • Jones, R.H.1
  • 31
  • 32
    • 0001604027 scopus 로고
    • Predictive model selection
    • Laud PW, Ibrahim JG,. Predictive model selection. J R Stat Soc B 1995; 57: 247-262.
    • (1995) J R Stat Soc B , vol.57 , pp. 247-262
    • Laud, P.W.1    Ibrahim, J.G.2
  • 34
    • 85010857362 scopus 로고
    • Why stepdown procedures in variable selection
    • Mantel N,. Why stepdown procedures in variable selection. Technometrics 1970; 15: 661-675.
    • (1970) Technometrics , vol.15 , pp. 661-675
    • Mantel, N.1
  • 36
    • 0027049043 scopus 로고
    • Building population pharmacokinetic-pharmacodynamic models. I. Models for covariate effects
    • Mandema JW, Verotta D, Sheiner LB,. Building population pharmacokinetic-pharmacodynamic models. I. models for covariate effects. J Pharmacokinet Biopharm 1992; 20: 511-528.
    • (1992) J Pharmacokinet Biopharm , vol.20 , pp. 511-528
    • Mandema, J.W.1    Verotta, D.2    Sheiner, L.B.3
  • 37
    • 84972488102 scopus 로고
    • Generalized additive models
    • Hastie T, Tibshirani R,. Generalized additive models. Stat Sci 1986; 3: 297-310.
    • (1986) Stat Sci , vol.3 , pp. 297-310
    • Hastie, T.1    Tibshirani, R.2
  • 38
    • 73349104384 scopus 로고    scopus 로고
    • Importance of shrinkage in empirical Bayes estimates for diagnostics: Problems and solutions
    • Savic RM, Karlsson MO,. Importance of shrinkage in empirical Bayes estimates for diagnostics: problems and solutions. AAPS J 2009; 11: 558-569.
    • (2009) AAPS J , vol.11 , pp. 558-569
    • Savic, R.M.1    Karlsson, M.O.2
  • 39
    • 0031784112 scopus 로고    scopus 로고
    • Automated covariate model building within NONMEM
    • Jonsson EN, Karlsson MO,. Automated covariate model building within NONMEM. Pharm Res 1998; 15: 1463-1468.
    • (1998) Pharm Res , vol.15 , pp. 1463-1468
    • Jonsson, E.N.1    Karlsson, M.O.2
  • 41
    • 84855962121 scopus 로고    scopus 로고
    • Objective Bayes model selection in probit models
    • Leon-Novelo L, Moreno E, Casella G,. Objective Bayes model selection in probit models. Statist Med 2012; 31: 353-365.
    • (2012) Statist Med , vol.31 , pp. 353-365
    • Leon-Novelo, L.1    Moreno, E.2    Casella, G.3
  • 42
    • 0001176385 scopus 로고
    • The best subset in multiple regression analysis
    • Garside MJ,. The best subset in multiple regression analysis. J R Stat Soc Ser C Appl Stat 1965; 14: 196-200.
    • (1965) J R Stat Soc ser C Appl Stat , vol.14 , pp. 196-200
    • Garside, M.J.1
  • 43
    • 51649109955 scopus 로고
    • All possible regressions with less computation
    • Furnival GM,. All possible regressions with less computation. Technometrics 1971; 13: 403-408.
    • (1971) Technometrics , vol.13 , pp. 403-408
    • Furnival, G.M.1
  • 44
    • 84947680781 scopus 로고
    • A tutorial on the SWEEP operator
    • Goodnight JH,. A tutorial on the SWEEP operator. Am Stat 1979; 33: 149-158.
    • (1979) Am Stat , vol.33 , pp. 149-158
    • Goodnight, J.H.1
  • 45
    • 84946633097 scopus 로고
    • Selection of the best subset in regression analysis
    • Hocking RR, Leslie RN,. Selection of the best subset in regression analysis. Technometrics 1967; 9: 531-540.
    • (1967) Technometrics , vol.9 , pp. 531-540
    • Hocking, R.R.1    Leslie, R.N.2
  • 46
    • 0016128505 scopus 로고
    • Regression by leaps and bounds
    • Furnival GM, Wilson RW Jr,. Regression by leaps and bounds. Technometrics 1974; 16: 499-511.
    • (1974) Technometrics , vol.16 , pp. 499-511
    • Furnival, G.M.1    Wilson, R.W.2
  • 47
    • 0018195038 scopus 로고
    • Efficient screening of nonnormal regression models
    • Lawless JF, Singhal K,. Efficient screening of nonnormal regression models. Biometrics 1978; 34: 318-327.
    • (1978) Biometrics , vol.34 , pp. 318-327
    • Lawless, J.F.1    Singhal, K.2
  • 48
    • 0034947990 scopus 로고    scopus 로고
    • Efficient screening of covariates in population models using Wald's approximation to the likelihood ratio test
    • Kowalski KG, Hutmacher MM,. Efficient screening of covariates in population models using Wald's approximation to the likelihood ratio test. J Pharmacokinet Pharmacodyn 2001b; 28: 253-275.
    • (2001) J Pharmacokinet Pharmacodyn , vol.28 , pp. 253-275
    • Kowalski, K.G.1    Hutmacher, M.M.2
  • 49
    • 84925623234 scopus 로고
    • Tests of statistical hypotheses concerning several parameters when the number of observations is large
    • Wald A,. Tests of statistical hypotheses concerning several parameters when the number of observations is large. Trans Am Math Soc 1943; 54: 426-482.
    • (1943) Trans Am Math Soc , vol.54 , pp. 426-482
    • Wald, A.1
  • 52
    • 85194972808 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • Tibshirani R,. Regression shrinkage and selection via the lasso. J R Stat Soc B 1996; 58: 267-288.
    • (1996) J R Stat Soc B , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 53
    • 34447116287 scopus 로고    scopus 로고
    • The lasso - A novel method for predictive covariate model building in nonlinear mixed effects models
    • Ribbing J, Nyberg J, Caster O, Jonsson EN,. The lasso-a novel method for predictive covariate model building in nonlinear mixed effects models. J Pharmacokinet Pharmacodyn 2007; 34: 485-517.
    • (2007) J Pharmacokinet Pharmacodyn , vol.34 , pp. 485-517
    • Ribbing, J.1    Nyberg, J.2    Caster, O.3    Jonsson, E.N.4
  • 54
    • 0031015557 scopus 로고    scopus 로고
    • The lasso method for variable selection in the Cox model
    • Tibshirani R,. The lasso method for variable selection in the Cox model. Stat Med 1997; 16: 385-395.
    • (1997) Stat Med , vol.16 , pp. 385-395
    • Tibshirani, R.1
  • 55
    • 1542784498 scopus 로고    scopus 로고
    • Variable selection via nonconcave penalized likelihood and its oracle properties
    • Fan J, Li R,. Variable selection via nonconcave penalized likelihood and its oracle properties. J Am Stat Assoc 2001; 96: 1348-1360.
    • (2001) J Am Stat Assoc , vol.96 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 56
    • 41049085169 scopus 로고    scopus 로고
    • Automated covariate selection and Bayesian model averaging in population PK/PD models
    • Lunn DJ,. Automated covariate selection and Bayesian model averaging in population PK/PD models. J Pharmacokinet Pharmacodyn 2008; 35: 85-100.
    • (2008) J Pharmacokinet Pharmacodyn , vol.35 , pp. 85-100
    • Lunn, D.J.1
  • 57
    • 0000343716 scopus 로고
    • Submodel selection and evaluation in regression - The X-random case
    • Breiman L, Spector P,. Submodel selection and evaluation in regression-the X-random case. Int Stat Rev 1992; 60: 291-319.
    • (1992) Int Stat Rev , vol.60 , pp. 291-319
    • Breiman, L.1    Spector, P.2
  • 58
    • 0027081755 scopus 로고
    • A bootstrap resampling procedure for model building: Application to the Cox regression model
    • Sauerbrei W, Schumacher M,. A bootstrap resampling procedure for model building: application to the Cox regression model. Stat Med 1992; 11: 2093-2109.
    • (1992) Stat Med , vol.11 , pp. 2093-2109
    • Sauerbrei, W.1    Schumacher, M.2
  • 59
    • 0030537683 scopus 로고    scopus 로고
    • Bootstrap model selection
    • Shao J,. Bootstrap model selection. J Am Stat Assoc 1996; 91: 655-665.
    • (1996) J Am Stat Assoc , vol.91 , pp. 655-665
    • Shao, J.1
  • 60
    • 0000626699 scopus 로고
    • Things i have learned (so far)
    • Cohen J,. Things I have learned (so far). Am Psychol 1990; 45: 1304-1312.
    • (1990) Am Psychol , vol.45 , pp. 1304-1312
    • Cohen, J.1
  • 62
    • 79551537566 scopus 로고    scopus 로고
    • Confirmatory analysis for phase III population pharmacokinetics
    • Hu C, Zhang J, Zhou H,. Confirmatory analysis for phase III population pharmacokinetics. Pharm Stat 2011; 10: 14-26.
    • (2011) Pharm Stat , vol.10 , pp. 14-26
    • Hu, C.1    Zhang, J.2    Zhou, H.3
  • 63
    • 0033213971 scopus 로고    scopus 로고
    • Stepwise selection in small data sets: A simulation study of bias in logistic regression analysis
    • Steyerberg EW, Eijkemans MJC, Habbema JDF,. Stepwise selection in small data sets: a simulation study of bias in logistic regression analysis. J Clin Epidemiol 1999; 52: 935-942.
    • (1999) J Clin Epidemiol , vol.52 , pp. 935-942
    • Steyerberg, E.W.1    Eijkemans, M.J.C.2    Habbema, J.D.F.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.