Statistical Methods for Survival Data Analysis 3rd phần 10 docx

Table B-8 (
continued
)
465
Table B-8 (
continued
)
466
467
Table B-8 (
continued
)
468
469
Table B-8 (
continued
)
470
471
Table B-8 (
continued
)
Source:
‘‘Estimation of Location and Scale Parameters by Order St
atistics from Singly and Doubly Censored Samples, Parts I a
nd II,’’ by A. E.
SarhanandB.G.Greenberg,Ann. Math. Statist.
, Vol. 27, pp. 427
—451
(1956). Reproduced by permission of the editor of the
Annals of

Mathematical Statistics.
472
Table B-9 Variances and Covariances of the Best Linear Est
imates of the Mean (
 ) and Standard Deviation (
 )for
Censored Samples Up to Size 20 from a Normal Population
473
Table B-9 (
continued
)
Source:
Up to n :
15 of this table is reproduced from A. E. Sarhan and B. G. G
reenberg, ‘‘Estimation of Location and Scale Parameters by O
rder Statistics
from Singly and Censored Samples, Parts I and II,’’
Ann. Math. Statist
., Vol. 27, pp. 427
—451 (1956),andVol.29,pp.79
—105
(1958), with permission of the
editor of the
Annals of Mathematical Statistics
. The rest of the table is produced from A. E. Sarhan and
B. G. Greenberg, ‘‘Estimation of Location and Scale
Parameters by Order Statistics from Singly and D
oubly Censored Samples, Part III,’’ Tech. Rep. 4-OOR, Proje
ct 1597, U.S. Army Research Office.
474

Table B-10 1/(1 9 R) and  for the Estimation of the Parameters of the Gamma
Distribution When There Are No Censored Observations
Source: ‘‘Estimation of Parameters of the Gamma Distribution Using Order Statistics,’’ by M. B.
Wilk, R. Gnanadesikan, and Marilyn J. Huyett, Biometrika, Vol. 49, pp. 525—545 (1962).
Reproduced by permission of the editor of Biometrika.
475
Table B-11  (P, S) and  (P, S) for Various Values of n/r: n/r : 1.0
For P - 0.52 read S from the left-hand margin, and for P .0.56 read S from the right-hand
margin. Note that the figures in region 2 are printed in bold roman type and those in region 3 in
bold italic type; the remainder of the table (outside of regions 2 and 3) is region 1.
476
Table B-11 (continued)
477
Table B-11 (continued)
478
Table B-11 (continued)
479
Table B-11 (continued)
480
Table B-11 (continued)
481
Table B-11 (continued)
482
Table B-11 (continued)
483
Table B-11 (continued)
484
Table B-11 (continued)
Source: ‘‘Estimation of Parameters of the Gamma Distribution Using Order Statistics,’’ by M. B.
Wilk, R. Gnanadesikan, and Marilyn J. Huyett, Biometrika, Vol. 49, pp. 525—545 (1962).

Reproduced by permission of the editor of Biometrika.
485
Table B-12 Percentage Points l

Such That P(
1
/
2
: l

) : 1 9 
Source: ‘‘Two Sample Test in the Weibull Distribution,’’ by D. R. Thoman and L. J. Bain,
Technometrics, Vol. 11, pp. 805—815 (1969). Reproduced by permission of the editor of Techno-
metrics.
486
Table B-13 Percentage Points z

Such That P(G : z

) : 1 9 
Source: ‘‘Two Sample Test in the Weibull Distribution,’’ by D. R. Thoman and L. J. Bain,
Technometrics, Vol. 11, pp. 805—815 (1969). Reproduced by permission of the editor of Techno-
metrics.
487
References
Aaronson, K. D., Schwartz, J. S., Chen, T. M., Wong, K. L., Goin, J. E, and Mancini,D.
M. (1997). Development and Prospective Validation of a Clinical Index to Predict
Survival in Ambulatory Patients Referred for Cardiac Transplant Evaluation.
Circulation, 95, 2660—2667.
Abramowitz, M., and Stegun, I. A. (1964). Handbook of Mathematical Functions with

Formulas, Graphs, and Mathematical Tables. Applied Mathematics Series 55.
National Bureau of Standards, Washington, DC.
Afifi, A. A., and Clark, V. (1990). Computer-Aided Multivariate Analysis, 2nd ed.
Lifetime Learning Publications, Belmont, CA.
Agresti, A. (1990). Categorical Data Analysis. Wiley, New York.
Aitchison, J. (1970). Statistical Problems of Treatment Allocation. Journal of the Royal
Statistical Society, Series A, 133, 206—238
Aitchison, J., and Brown, J. A. C. (1957). The Lognormal Distribution. Cambridge
University Press, Cambridge.
Aitchison, J., and Silvey, S. D. (1957). The Generalization of Probit Analysis to the Case
of Multiple Responses. Biometrika, 44, 131—140.
Aitkin, M., Laird, N., and Francis, B. (1983). A Reanalysis of the Stanford Heart
Transplant Data (with discussion). Journal of the American Statistical Association,
78, 264—292.
Akaike, H. (1969). Fitting Autoregressive Models for Prediction. Annals of the Institute
of Statistical Mathematics, 21, 243—247.
Akaike, H. (1974). A New Look at the Statistical Model Identification. IEEE Transac-
tions on Automatic Control, AC-19, 716—723.
Albert, I. J. (2000). The Use of Frailty Models in Genetic Studies: Application to the
Relationship between End-Stage Renal Failure and Mutation Type in Alport
Syndrome. European Community Alport Syndrome Concerted Action Group
(ECASCA). Journal of Epidemiology and Biostatistics, 5(3), 169—175.
Albertson, P. C., Hanley, J. A., Gleason, D. F., and Barry, M. J. (1998). Competing Risk
Analysis of Men Aged 55 to 74 Years at Diagnosis Managed Conservatively for
Clinically Localized Prostate Cancer. Journal of the American Medical Association,
280(11),975—980.
488
Alioum, A., and Commenges, D. (1996). A Proportional Hazards Model for Arbitrarily
Censored and Truncated Data. Biometrics, 52, 512—524.
Altshuler, B. (1970). Theory for Measurement of Competing Risks in Animal Experi-

ments. Mathematical Biosciences, 6,1—11.
Ananth, C. V., and Kleinbaum, D. G. (1977). Regression Models for Ordinal Data: A
Review of Methods and Application. International Journal of Epidemiology, 26,
1323—1333.
Andersen, P. K. (1982). Testing Goodness of Fit of Cox’s Regression Model. Biometrics,
38,67—77.
Andersen, P. K. (1992). Repeated Assessment of Risk Factors in Survival Analysis.
Statistical Methods in Medical Research, 1,297—315
Andersen, P. K., Borgan, O., Gill, R. D., and Keiding, N. (1993). Statistical Models
Based on Counting Processes. Springer-Verlag, New York.
Andersen, P. K., and Gill, R. D. (1982). Cox’s Regression Model Counting Process: A
Large Sample Study. Annals of Statistics, 10, 1100—1120
Anderson, J. A. (1972). Separate Sample Logistic Discrimination, Biometrika, 59,19—35.
Andrews, D. F., and Herzberg, A. M. (1985). Data: A Collection of Problems from Many
Fields for the Student and Research Worker. Springer-Verlag, New York.
ARIC Investigators. (1989). The Atherosclerosis Risk in Communities (ARIC) Study:
Design and Objectives. American Journal of Epidemiology, 129, 687—702.
Arjas, E. (1988). A Graphical Method for Assessing Goodness of Fit in Cox’s
Proportional Hazards Model. Journal of the American Statistical Association, 83,
204—212.
Armitage, P. (1959). The Comparison of Survival Curves. Journal of the Royal
Statistical Society, Series A, 122, 279—300.
Armitage, P. (1971). Statistical Methods in Medical Research. Blackwell Scientific
Publications, Oxford.
Armitage, P. (1981). Importance of Prognostic Factors in the Analysis of Data from
Clinical Trials. Controlled Clinical Trials, 1, 347—353.
Armitage, P., and Gehan, E. A. (1974). Statistical Methods for the Identification and
Use of Prognostic Factors. International Journal of Cancer, 13,16—35.
Asal, N. R., Geyer, J. R., Risser, D. R., Lee, E. T., Kadamani, S., and Cherng, N. (1988a).
Risk Factors in Renal Cell Carcinoma, Part I. Methodology, Demographics,

Tobacco, Beverage and Obesity. Cancer Detection and Prevention, 11, 359—377.
Barnard, G. A. (1963). Some Aspects of the Fiducial Argument. Journal of the Royal
Statistical Society, Series B, 34, 216—217.
Bartholomew, D. J. (1957). A Problem in Life Testing. Journal of the American
Statistical Association, 52, 350—355.
Bartholomew, D. J. (1963). The Sampling Distribution of an Estimate Arising in Life
Testing. Technometrics, 5, 361—374.
Baumgartner, R. N., Roche, A. F., et al. (1987). Fatness and Fat Patterns: Associations
with Plasma Lipids and Blood Pressure in Adults, 18 to 57 Years of Age. American
Journal of Epidemiology, 126, 614—628.
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