Editorial Type:
Article
Article Type:
Research Article

Parallels between Statistical Issues in Medical and Meteorological Experimentation

K. Ruben Gabriel Department of Mathematics, University of Rochester, Rochester, New York

Search for other papers by K. Ruben Gabriel in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Nov 2000
DOI:
https://doi.org/10.1175/1520-0450(2000)039<1822:PBSIIM>2.0.CO;2
Page(s):
1822–1836
Restricted access

Abstract

The methodology of experimentation, randomization, and statistical analysis in weather modification has many parallels in clinical trials, such as the need for randomization, and the question of inclusion or exclusion of units assigned to be treated but not actually treated. There also are considerable differences, mainly in the definition of units, where the obvious choice of a single patient is in contrast with the highly problematic definition of a cloud or storm, and in the ethical aspects. This paper highlights some of these parallels and differences in the hope that looking at one’s own problems in a different context may enhance one’s understanding. It may also reconcile experimenters to their need for statistics: as the Hebrew saying goes, “Tzarat rabim, hatzi nehama” (the misfortune of many is half a consolation).

DEDICATION

It has been my good fortune to have worked with meteorologists who had an appreciation of what statistics could do for them and even seemed to get pleasure from understanding it. Such was Graeme Mather: not only did he seek and heed statistical support for his seminal work in cloud seeding, but he conveyed a sense of enjoying the cooperation and intellectual exchange. When we collaborated, I was challenged to propose and to justify new methods of analysis—as in exploring Nelspruit rainfall by means of biplots and linear models () and in a joint attempt, by e-mail, to apply QQ-plots to the study of detailed differences between the rain distributions of seeded and unseeded storms—and I was gratified to see his intelligent and useful application of these analyses. Graeme not only made his own important contributions but also had a singular gift of making others feel that he understood and appreciated them. It is appropriate to dedicate the following paper to him, not only because I have learned much of what I write about from collaborating with him and other like-minded meteorologists, but also because he was present when I delivered the initial version in Bari, Italy, in 1996 and was generous in expressing his appreciation. I miss him.

Corresponding author address: K. Ruben Gabriel, Department of Mathematics, University of Rochester, Rochester, NY 14627.

krg1@troi.cc.rochester.edu.

Abstract

The methodology of experimentation, randomization, and statistical analysis in weather modification has many parallels in clinical trials, such as the need for randomization, and the question of inclusion or exclusion of units assigned to be treated but not actually treated. There also are considerable differences, mainly in the definition of units, where the obvious choice of a single patient is in contrast with the highly problematic definition of a cloud or storm, and in the ethical aspects. This paper highlights some of these parallels and differences in the hope that looking at one’s own problems in a different context may enhance one’s understanding. It may also reconcile experimenters to their need for statistics: as the Hebrew saying goes, “Tzarat rabim, hatzi nehama” (the misfortune of many is half a consolation).

DEDICATION

It has been my good fortune to have worked with meteorologists who had an appreciation of what statistics could do for them and even seemed to get pleasure from understanding it. Such was Graeme Mather: not only did he seek and heed statistical support for his seminal work in cloud seeding, but he conveyed a sense of enjoying the cooperation and intellectual exchange. When we collaborated, I was challenged to propose and to justify new methods of analysis—as in exploring Nelspruit rainfall by means of biplots and linear models () and in a joint attempt, by e-mail, to apply QQ-plots to the study of detailed differences between the rain distributions of seeded and unseeded storms—and I was gratified to see his intelligent and useful application of these analyses. Graeme not only made his own important contributions but also had a singular gift of making others feel that he understood and appreciated them. It is appropriate to dedicate the following paper to him, not only because I have learned much of what I write about from collaborating with him and other like-minded meteorologists, but also because he was present when I delivered the initial version in Bari, Italy, in 1996 and was generous in expressing his appreciation. I miss him.

Corresponding author address: K. Ruben Gabriel, Department of Mathematics, University of Rochester, Rochester, NY 14627.

krg1@troi.cc.rochester.edu.

Save
Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Beach, M. L., and P. Meier, 1989: Choosing covariates in the analysis of clinical trials. Controlled Clin. Trials,10, 161S–175S.

  • Berthoumieu, J.-F., A. Loretz, A. Carlier, F. Abdellani, E. Lambert, J.-R. Mathieu, and K. R. Gabriel, 1999: Cloud base hygroscopic seeding to reduce hail in the south-west of France. Concepts and first results. ACMG Compte rendu d’activité, 4 pp. [Available from J.-F. Berthoumieu, ACMG, Aerodrome de Agen, Agen, France.].

  • Bradley, R. A., S. S. Srivastava, and A. Lanzdorf, 1980: Some approaches to statistical analysis of a weather modification experiment. Statistical Analysis of Weather Modification Experiments, E. J. Wegman and D. J. DePriest, Eds., Marcel Dekker, 33–53.

  • Braham, R. R., 1979: Field experimentation in weather modification. J. Amer. Stat. Assoc.,74, 57–104.

  • Brendler, C. B., and P. C. Walsh, 1992: The role of radical prostatectomy in the treatment of prostate cancer. CA—Cancer J. Clin.,42, 213–222.

  • Bruintjes, R. T., D. W. Breed, G. B. Foote, M. J. Dixon, B. G. Brown, V. Salazar, and J. R. Rodriguez, 1999: Program for the augmentation of rainfall Coahuila (PARC): Overview and design. Preprints, Seventh WMO Scientific Conf. on Weather Modification, Chiang-Mai, Thailand, World Meteorological Organization, 53–59.

  • Changnon, S. A., and Coauthors, 1977: Hail suppression: Impacts and issues. Results from the 1989 Exploratory Cloud Seeding Experiment in Illinois, Illinois State Water Survey, 427 pp.

  • ——, R. R. Czys, K. R. Gabriel, M. S. Petersen, R. W. Scott, and N. E. Westcott, 1993: Results from the 1989 Exploratory Cloud Seeding Experiment in Illinois. Illinois State Water Survey, 154 pp.

  • ——, K. R. Gabriel, N. E. Westcott, and R. R. Czys, 1995: Exploratory analysis of seeding effects on rainfall: Illinois 1989. J. Appl. Meteor.,34, 1215–1224.

  • Cox, C., H. T. Davis, J. F. Calimlim, W. M. Wardell, and L. Lasagna, 1980: Use of the biplot for graphical display and analysis of multivariate pain data in clinical analgesic trials. Controlled Clin. Trials,7, 63–64.

  • Cox, D. R., and D. Oakes, 1984: Analysis of Survival Data. Chapman and Hall, 201 pp.

  • Davis, B. R., and R. J. Hardy, 1990: Upper bounds for type I and type II error rates in conditional power calculations. Commun. Stat.,A19, 3571–3584.

  • Dennis, A., 1980: Weather Modification by Cloud Seeding. Academic Press, 267 pp.

  • Epstein, B. E., and G. E. Hanks, 1992: Prostate cancer: Evaluation and radiotherapeutic management. CA—Cancer J. Clin.,42, 223–240.

  • Fleming, T. R., and D. L. DeMets, 1996: Surrogate end points in clinical trials: Are we being misled? Ann. Intern. Med.,125, 605–613.

  • Francis, C. W., V. D. Pellegrini, V. J. Marder, S. Totterman, C. M. Harris, K. R. Gabriel, M. V. Azodo, and M. V. Leibert, 1992: Comparison of Warfarin and external pneumatic compression in prevention of venous thrombosis after total hip replacement. J. Amer. Med. Assoc.,267, 2911–2915.

  • Gabriel, K. R., 1967: The Israeli artificial rainfall stimulation experiment: Statistical evaluation of the period 1961–1965. Proceedings Fifth Berkeley Symposium on Math. Stat. and Prob., L. LeCam and J. Neyman, Eds., Vol. V, Weather Modification, University of California Press, 91–114.

  • ——, 1995: Climax again? J. Appl. Meteor.,34, 1225–1227.

  • ——, 1999: Ratio statistics for randomized experiments in precipitation stimulation. J. Appl. Meteor.,38, 290–301.

  • ——, and P. Feder, 1969: On the distribution of statistics suitable for evaluating rainfall stimulation experiments. Technometrics,11, 149–160.

  • ——, and M. Baras, 1970: The Israeli rainmaking experiment 1961–67. Final statistical tables and evaluation. Tech. Rep., Dept. of Statistics, Hebrew University, Jerusalem, Israel, 40 pp. [Available from K. R. Gabriel, Dept. of Mathematics, University of Rochester, Rochester, NY 14627.].

  • ——, and S. A. Changnon Jr., 1982: Piggyback weather experimentation: Superimposing randomized treatment comparisons on commercial cloud seeding operations. J. Wea. Mod.,13, 7–10.

  • ——, and G. K. Mather, 1986: Exploratory analysis of 1951–1982 summer rainfall data around Nelspruit, Transvaal and of possible effects of 1972–1981 cloud seeding. J. Climate Appl. Meteor.,25, 1077–1087.

  • ——, and D. Rosenfeld, 1990: The second Israeli rainfall stimulation experiment: Analysis of precipitation on both targets. J. Appl. Meteor.,29, 1055–1069.

  • Gilbert, J. P., B. McPeek, and F. Mosteller, 1977: Statistics and ethics in surgery and anesthesia. Science,198, 684–689.

  • Hills, M., and P. Armitage, 1979: The two-period cross-over clinical trial. Brit. J. Pharmac.,8, 7–20.

  • Kempthorne, O., 1980: Some statistical aspects of weather modification studies. Statistical Analysis of Weather Modification Experiments, E. J. Wegman and D. J. DePriest, Eds., Marcel Dekker, 89–107.

  • Levin, Z., Y. Yin, Z. Levin, T. G. Reisen, and S. Tzivion, 1999: Comparison of the effects of hygroscopic and glaciogenic seeding on the evolution of the spectra of cloud and precipitation particles in convective clouds. Preprints, Seventh WMO Scientific Conf. on Weather Modification, Chiang-Mai, Thailand, World Meteorological Organization, 73–74.

  • List, R., K. R. Gabriel, B. A. Silverman, Z. Levin, and T. Karakostas, 1999: The rain enhancement experiment in Puglia, Italy: Statistical evaluation. J. Appl. Meteor.,38, 281–289.

  • Mather, G. K., D. E. Terblanche, F. E. Steffens, and L. E. Fletcher, 1997: Results of the South African cloud-seeding experiments using hygroscopic flares. J. Appl. Meteor.,36, 1433–1447.

  • Mielke, P. W., 1985: Design and evaluation of weather modification experiments. Probability, Statistics, and Decision Making in the Atmospheric Sciences, A. H. Murphy and R. W. Katz, Eds., Westview Press, 439–459.

  • ——, 1995: Comments on the Climax I and II experiments including replies to Rangno and Hobbs. J. Appl. Meteor.,34, 1228–1232.

  • Miller, A. J., D. E. Shaw, L. G. Veitch, and E. J. Smith, 1979: Analyzing the results of a cloud-seeding experiment in Tasmania. Commun. Stat.,A8, 1017–1047.

  • Moran, P. A. P., 1959: The power of a cross-over test for the artificial stimulation of rain. Austral. J. Stat.,1, 47–52.

  • Multicenter Diltiazem Post-Infarction Trial Research Group, 1988: The effect of Diltiazem on mortality and reinfarction after myocardial infarction. New England J. Med.,319, 385–392.

  • New York Times, 1999: Sham surgery returns as a research tool. N.Y. Times Week Rev., 25 April 1999, 3.

  • Neyman, J., 1977: A statistician’s view of weather modification technology (a review). Proc. Nat. Acad. Sci.,74, 4714–4721.

  • Nori, D., 1993: 3-D conformal brachytherapy is lower-cost, outpatient Ca treatment. Oncol. News Int.,2, 3–22.

  • Oakes, D., 1993: The logic and role of meta-analysis in clinical research. Stat. Methods Med. Res.,2, 147–160.

  • ——, and Coauthors, 1993: Use of compliance measures in an analysis of the effect of Diltiazem on mortality and reinfarction after myocardial infarction. J. Amer. Stat. Assoc.,88, 44–49.

  • O’Brien, P. C., and T. R. Fleming, 1979: A multiple testing procedure for clinical trials. Biometrics,35, 549–556.

  • Orville, H. D., 1996: A review of cloud seeding modeling in weather modification. Bull. Amer. Meteor. Soc.,77, 1535–1555.

  • Piantadosi, S., 1997: Clinical Trials. A Methodologic Perspective. John Wiley and Sons, 590 pp.

  • Rangno, A. L., and P. V. Hobbs, 1993: Further analyses of the Climax cloud-seeding experiments. J. Appl. Meteor.,32, 1837–1847.

  • ——, and ——, 1995: Reply. J. Appl. Meteor.,34, 1233–1238.

  • Rosenfeld, D., and W. L. Woodley, 1989: Effects of cloud seeding in west Texas. J. Appl. Meteor.,28, 1050–1080.

  • ——, and R. Nirel, 1996: Seeding effectiveness—The interaction of desert dust and the southern margins of rain cloud systems in Israel. J. Appl. Meteor.,35, 1502–1510.

  • Schmid, P., 1967: On “Grossversuch III”; A randomized hail suppression experiment in Switzerland. Proceedings Fifth Berkeley Symposium on Math. Statist. and Prob., L. LeCam and J. Neyman, Eds., Vol. V, Weather Modification, University of California Press, 141–159.

  • Senn, S. J., 1993: Cross-Over Trials in Clinical Research. John Wiley and Sons, 296 pp.

  • ——, 1997: Statistical Issues in Drug Development. John Wiley and Sons, 423 pp.

  • Silverman, B. A., 1999: An independent statistical re-evaluation of the South African hygroscopic flare seeding experiment. Preprints, Seventh WMO Scientific Conf. on Weather Modification, Chiang-Mai, Thailand, World Meteorological Organization, 45–48.

  • ——, W. Sukarmjanaset, D. Rosenfeld, and R. Talumassawadti, 1999:The Thailand warm cloud seeding experiment. Preprints, Seventh WMO Scientific Conf. on Weather Modification, Chiang-Mai, Thailand, World Meteorological Organization, 9–12.

  • Steering Committee of the Physicians’ Health Study, 1989: Final report on the aspirin component of the ongoing Physicians’ Health Study. New England J. Med.,321, 129–135.

  • Tukey, J. W., J. R. Brillinger, and L. V. Jones, 1978: Report of the Statistical Task Force to The Weather Modification Board. Vol. II. U.S. Government Printing Office, 94 pp.

  • Wegman, E. J., and D. J. DePriest, Eds., 1980: Statistical Analysis of Weather Modification Experiments. Marcel Dekker, 145 pp.

  • Woodley, W. L., J. Jordan, A. Barnston, J. Simpson, R. Biondini, and J. Flueck, 1982: Rainfall results of the Florida Area Cumulus Experiment, 1970–78. J. Appl. Meteor.,21, 139–164.

  • ——, D. Rosenfeld, R. Lahav, P. Sudhikoses, N. Tantipubthong, and W. Sukarmjanaset, 1999: The Thailand cold-cloud seeding experiment. Preprints, Seventh WMO Scientific Conf. on Weather Modification, Chiang-Mai, Thailand, World Meteorological Organization, 21–32.

  • Yin, Y., Z. Levin, T. G. Reisen, and S. Tzivion, 1999: A numerical evaluation of seeding with hygroscopic flares: Sensitivity to seeding time, seeding height, seeding amounts, size of particles, and environmental shear. Preprints, Seventh WMO Scientific Conf. on Weather Modification, Chiang-Mai, Thailand, World Meteorological Organization, 69–74.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 291 64 2
PDF Downloads 53 12 0