LogtransformationsAllometric ModelsBiblio.pdf
© 2013 Timothy G. Gregoire, Yale University
Last revised: September 2013
Log Transformations/Allometric Models
(76 entries)
Articles:
1. Misc. 1. Back log transformation.
2. Williams, C.B. 1937. “The use of logarithms in the interpretation of certain
entomological problems”. In The Annals of Applied Biology (Brierley, W.B. and
Gimingham, C.T. eds.). Vol. XXIV. Cambridge, At the University Press.
3. Meyer, H.A. 1938. “The standard error of estimate of tree volume from the
logarithmic volume equation”. J. For. 36: 341-342
4. Finney, D.J. 1941. “On the distribution of a variate whose logarithm is normally
distributed”. Supplement to the Journal of the Royal Statistical Society 7(2): 155 –
161
5. Stevens, W.L. 1951. “Asymptotic Regression”. Biometrics 7 (3): 247 – 267.
6. Neyman, J. and Scott, E.L. 1960. “Correction for Bias Introduced by a
transformation of variables”. Annals of Mathematical Statistics 31(3): 643 – 655
7. Schmetterer, L. 1960. “On a problem of J. Neyman and E.Scott”. Annals of
Mathematical Statistics 31(3): 656 – 661
8. Laurent, A.G. 1963. “The lognormal distribution and the translation method:
description and estimation problems”. Journal of the American Statistical
Association 622: 231 – 235
9. Mostafa, M.D. and Mahmoud, M.W. 1963. “On the problem of estimation for the
bivariate lognormal distribution”. Miscellanea: 522 – 527
10. Meulenberg, M.T.G. 1965. “On the estimation of an exponential function”.
Econometrica 33(4): 863-867
11. Patterson, R.L. 1966. “Difficulties involved in the estimation of population mean
using transformed sample data”. Technometrics 8(3): 535 – 537
12. Glass, N.R. 1967. “A technique for fitting nonlinear models to biological data”.
Ecology 48(6): 1010- 1013
13. Goldberger, A. 1968. “The interpretation and estimation of Cobb-Douglas
functions”. Econometrica 35 (3-4): 464 – 472
© 2009 Timothy G. Gregoire
Logtransformations/Allometric Models
© 2009, Timothy G. Gregoire, Yale University 2
14. Heien, D.M. 1968. “A note on Log-linear regression”. Journal of the American
Statistical Association 63(323): 1034 – 1038.
15. Zar, J.H. 1968. “Calculation and miscalculation of the Allometric equation as a
model in biological data”. BioScience 18(2): 1118 – 1119
16. Aitchison, J. and Brown, J.A.C. 1969. “The lognormal distribution”. Cambridge
University Press, Cambridge.
17. Draper, N.R. and Cox, D.R. 1969. “On Distribution and their transformation to
normality”. Journal of the ROYAL Statistical Society, Series B, 31:472-476
18. Hafley, W.L. 1969. “Calculation and miscalculation of the allometric equation
reconsidered”. Bioscience 19(11): 974 – 983
19. Bradu, D. and Mundlak, Y. 1970. “Estimation of lognormal linear models”.
Journal of the American Statistical Association 65 (329): 198-211
20. Dixon, P.M. and Newman, M.C. 1970. “Correcting statistical biases in logtransformed data corrections for small sample sizes”. Savannah River Ecology
Laboratory, University of Georgia.
21. Mosimann, J.E. 1970. “Size allometry: size and shape variables with
characterizations of the lognormal and Generalized Gamma distribution”. Journal
of the American Statistical Association 65(330): 930 - 945
22. Andrews, D.F. 1971. “A note on the selection of data transformations”.
Biometrika 58(2): 249-254
23. Jolicoeur, P. and Heusner, A.A. 1971. “The Allometry equation in the analysis of
the standard oxygen consumption and body weight of the white rat”. Biometrics
27: 841 – 55
24. Baskerville, G.L. 1972. “Use of logarithmic regression in the estimation of plant
biomass”. Canadian Journal of Forest Research 2: 49 – 53
25. Carlson, B.C. 1972. “The Logarithmic Mean”. American Mathematical Monthly
79(6): 615-618
26. Land, C.E. 1972. “An evaluation of approximate confidence interval estimation
methods for lognormal means”. Technometrics 14(1): 145-158
27. Teekens, R. and Koerts, J. 1972. “Some statistical implications of the log
transformation of multiplicative models”. Econometrica 40(5): 793 – 819
© 2012 Timothy G. Gregoire
Logtransformations/Allometric Models
© 2009, Timothy G. Gregoire, Yale University 3
28. Beauchamp, J.J. and Olson, J.S. 1973. “Corrections for bias in regression
estimates after logarithmic transformation”. Ecology 54(6): 1403 – 1407
29. Mountford, M.D. and Bunce, R.G.H. 1973. “Regression sampling with
allometrically related variables, with particular reference to production studies”.
Forestry 46(2): 203 – 212
30. Baskerville, G.L. 1974. “Use of logarithmic regression in the estimation of plant
biomass: Reply”. Can. J. For. Res. 4(149)
31. Evans, I.G. and Shaban, S.A. 1974. “A note on estimation in lognormal models”.
Journal of the American Statistical Association (Theory and Methods) 69(347):
779 – 781
32. Kowaliski, C.J. and Guire, K.E. 1974. “Longitudinal data analysis”. Growth 38:
131 – 169
33. Land, C.E. 1974. “Confidence interval estimation for means after data
transformations to normality”. Journal of the American Statistical Association
(Theory and Methods) 69(347): 795 – 802
34. Munro, D.D. 1974. “Use of logarithmic regression in the estimation of plant
biomass: Discussion”. Can. J. For. Res. 4 (149).
35. Evans, I.G. and Shaban, S.A. 1976. “Point estimation in multiplicative models”.
Econometrica 44(3): 467 – 473.
36. Mosteller, F. and Tukey, J. W. 1977. “Chapter 6: General Hints when Reexpressed carrier is log x”. Data Analysis and Regression: a second course in
statistics. Addison Wesley Publishing Company: Reading, Mass.
37. Mohn, E. 1979. “Confidence estimation of measures of location in the log normal
distribution”. Biometrika 66(3): 567-575
38. Wiant, H.V. Jr., and Harner, E. J. 1979. “Percent bias and standard error in
logarithmic regression”. Forest Science 25(1): 167 - 168
39. Amemiya, T. 1980. “Selection of Regressors”. International Economic Review
21(2): 331-353
40. Flewelling, J.W. 1981. “Multiplicative regression with lognormal errors”. Forest
Science 27(2): 281-289
41. Godfrey, L.G. 1981. “Testing linear and log-linear regressions for functional
from”. Review of Economic Studies XLVIII: 487 – 496.
© 2012 Timothy G. Gregoire
Logtransformations/Allometric Models
© 2009, Timothy G. Gregoire, Yale University 4
42. Payandeh, B. 1981. “Choosing Regression Models for Biomass Prediction
Equations”. The Forestry Chronicle: 229 – 232.
43. Hepp, T.E. 1982. “Estimating crown biomass in loblolly pine plantations in the
Carolina Flatwoods”. Forest Science 28(1): 115 – 127.
44. Lee, C.Y. 1982. “Comparison of two correction methods for the bias due to the
logarithmic transformation in the estimation of biomass”. Can. J. For. Res. 12:
326 – 331
45. Duan, N. 1983. “Smearing estimate: A nonparametric retransformation method”.
Journal of American Statistical Association 78(373): 605 – 610.
46. Kennedy, P. 1983. “Practitioner’s corner: logarithmic dependent variables and
prediction bias”. Oxford Bulletin of Economics and Statistics 45: 389 – 392
47. Sprugel, D.G. 1983. “Correcting for bias in log-transformed allometric
equations”. Ecology 64(1): 209 – 210
48. Miller, D.M. 1984. “Reducing Transformation Bias in Curve Fitting”. The
American Statistician 38(2): 124 – 126.
49. Ferguson, R.I. 1986. “River load underestimated by rating curves”. Water
Resources Research 22(1): 74-76
50. Stynes, D.J., Peterson, G.L., and Rosenthal, D.H. 1986. “Log Transformation Bias
in Estimating Travel Cost Models”. Land Economics 62(1): 94-103
51. Taylor, J.M.G. 1986. “The retransformed mean after a fitted power
transformation”. Journal of American Statistical Associations (Theory and
Methods) 81(393): 114-118
52. Berry, D.A. 1987. “Logarithmic transformation in ANOVA”. Biometrics 43: 439
– 456
53. Ung, C.H. and Vegiard, S. 1988. “Problèmès d’infèrence relies à la
transformation logarithmique en regression”. Canadian Journal 18: 733 – 738.
54. Powell, S. 1991. “Implementation in the SAS system of the Bradu and Mundlak
minimum variance unbiased estimator of the mean of a lognormal distribution”. A
paper presented at the SAS Users Group International 16TH Annual Conference,
February 17-20, 1991
55. Snowdon, P. 1991. “A ratio estimator for bias correction in logarithmic
regressions”. Can. J. For. Res. 21: 720 – 724
© 2012 Timothy G. Gregoire
Logtransformations/Allometric Models
© 2009, Timothy G. Gregoire, Yale University 5
56. Greene, W.H. 1993. “Chapter 7: Hypothesis tests with the Multiple Regression
Model in Econometric Analysis (2nd Edition)”. Macmillan Publishing Company.
57. Smith, R.J. 1993. “Logarithmic transformation Bias in Allometry”. American
Journal of Physical Anthropology 90: 215-228
58. Vegiard, S. and Ung, C.H. 1993. “Statistical inference problems related to the
logarithmic transformation in regression: another method of interval estimation”.
Can. J. For. Res. 23: 871 – 872
59. Hayes, D.B. and Brodziak, J.K.T. 1995. “Efficiency and bias of estimators and
sampling designs for determining length-weight relationships of fish”. Can. J.
Fish. Aquat. Sci. 52: 84 – 92
60. Keene, O.N. 1995. “The log transformation is special”. Statistics in Medicine
14:811 – 819
61. Sakia, R.M. 1995. “An empirical comparison of three bias estimating procedures
due to retransformation”. Informatik, Biometrie und Epidemiologie in Medizin
und Biologie 26(1): 1-6.
62. Oaten, A.S. 1996. “Sequential Estimation of Log(Abundance)”. Biometrics 52: 38
– 49.
63. El-Shaarawi, A.H. and Viveros, R. 1997. “Inference about the mean in logregression with environmental applications”. Environmetrics 8:569 - 582
64. Hayes, D.B. and Brodziak, J.K.T. 1997. “Reply: Efficiency and bias of estimators
and sampling designs for determining length-weight relationships of fish”. Can. J.
Fish. Aquat. Sci. 54: 744 – 745
65. Manning, W.G. 1998. “The logged dependent variable, heteroscedasticity, and the
retransformation problem”. Journal of Health Economics 17: 283 – 295
66. Mullahy, J. 1998. “Much ado about two: reconsidering retransformation and the
two-part model in health econometrics”. Journal of Health Economics 17: 247281
67. Ai, C. and Norton, E.C. 2000. “Standard errors for the retransformation problem
with heteroscedasticity”. Journal of Health Economics 19: 697 – 718
68. Cole, T.J. 2000. “Sympercents: symmetric percentage differences on the 100 loge
scale simplify the presentation of log-transformed data”. Statistics in Medicine 19:
3109 – 3125
69. Van Belle, G. 2002. Statistical Rules of Thumb. Wiley. Pp. 104 – 109
© 2012 Timothy G. Gregoire
Logtransformations/Allometric Models
© 2009, Timothy G. Gregoire, Yale University 6
70. Bhaumik, D.K. and Gibbons, R.D. 2004. “An upper prediction limit for the
arithmetic mean of a lognormal random variable”. Technometrics 46(2): 23971. Lindsey, J.K. 2004. Introduction to Applied Statistics: A Modeling Approach
(Chapter: Transforming the response). Oxford University Press.
72. Zou, G.Y., Huo, C.Y. and Taleban, J. 2009. “Simple confidence intervals for
lognormal means and their differences with environmental applications”.
Environmetrics 20: 172 – 180.
73. Zou, G.Y., Taleban, Y. and Huo, C.Y. 2009. “Confidence interval estimation for
lognormal data with application to health economics”. Computational Statistics
and Data Analysis 53: 3755 – 3764.
74. Robert, B., Hara, O. and Kotze, D.J. 2010. “Do not log-transform count data”.
Methods of Ecology and Evolution 1: 118 -122.
75. Das, R.N. and Park, J.S. 2011. “Discrepancy in regression estimates between lognormal and gamma: Some case studies”. Journal of Applied Statistics: 1-15.
76. Krishnamoorthy, K., Mallick, A. and Mathew, T. 2011. “Inference for the
Lognormal Mean and Quantiles based on Samples with Left and Right I
Censoring”. Technometrics 53: 72 – 83.
© 2012 Timothy G. Gregoire