The other, by Martin T. Schechter et al., also rebukes Duesberg in the final paragraph: "It is a disservice to the many people infected with HIV-1 and a hindrance to public health initiatives for scientists to claim that HIV-1 is harmless and not aetiologically related to AIDS" (Martin T. Schechter et al., "HIV-1 and the aetiology of AIDS," Lancet, 13 March 1993).

Both studies are forms of survey research, my profession since 1966. In a letter to me (14 April 1993), Martin Schechter denies this, which merely indicates his ignorance of basic concepts. In survey research, data from a selected sample are projected to represent a greater universe or population. As explained in one of the classic texts of my field:

"Sampling, as probably everyone knows, arises from the impossibility or impracticability of studying an entire population. It is not very feasible, if at all possible, to study the entire population of the United States at a given time, nor is it necessary to test the entire contents of a well-sifted grain barrel to determine its quality content. Even where it is advisable to study an entire population, time and cost elements are usually prohibitive. Essentially. sampling is a problem in inference, the aim being to secure sufficient information from a representative segment of the population to enable one to infer the true state of affairs with respect to the characteristics under observation for the entire population within a certain range of error." (Robert Ferb, Statistical Techniques in Market Research, New York, 1949)

Both studies claim to support the HIV-AIDS hypothesis. Both studies are highly implausible, if for no other reason, because they show that drugs don't do anything. But drugs are not sugar pills, and there are physical consequences to putting them in human bodies.

After reading the two brief reports, I had grave doubts that the researchers understood how to design, conduct, or analyze survey research. I wrote to Ascher and Schechter, asking permission to look at raw data, questionnaires, and other study materials. Ascher did not reply. Schechter wrote:

"Unfortunately, your request to inspect our raw data and other documents is problematic. As you are no doubt aware, there are tremendous concerns surrounding confidentiality in studies of this type. In our informed consent, we have specifically promised not only all the participants but their practitioners that the data we collect will not be seen by any individuals or agencies outside the investigators involved in the study. To allow anyone else to inspect the raw data would constitute a breach of this fundamental promise."

Schechter ignored the most specific request I made in my letter: a copy of the self-administered questionnaire he mentioned in his article. I fail to see how the release of a blank questionnaire or of data, consisting of grouped numbers, could violate promises of confidentiality. Apparently Schechter expects us to accept his research on faith.

One of the cardinal principles of science is openness, which means sharing data and describing methodology in sufficient detail that a study could be replicated or in some other way verified. Although replication might not be possible or practical, there is another way the worth of the data could be evaluated through validation.

In professional survey research, it is the practice to validate all studies, using sophisticated techniques. Let's suppose that an in-person survey was conducted by local interviewers in a dozen cities around the country. After the questionnaires have come back from the field, interviewers from the home office, using WATS lines, validate a percentage of each interviewer's work. This means calling respondents and asking a few questions designed to ascertain that the rules of the study were followed. If even a single questionnaire fails the validation test, then validation is performed upon 100% of that interviewer's work. In the extremely rare event that cheating is discovered, the culprits are severely punished.

An unvalidated survey has little or no credibility. Since neither the Ascher nor the Schechter study is even open to validation, they deserve to be rejected on this basis alone. In addition, neither author describes the characteristics of the samples, so one has no idea how representative they might be of the populations from which they were allegedly drawn.

It has been my experience as an analyst, without exception, that when data don't make sense it is because there is something wrong with them. It doesn't make sense that a single, biochemically inactive microbe could be the cause of the 29 (at last count) AIDS-indicator diseases. And it doesn't make sense that drugs don't do anything.