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PubMed1995

MedCalc: a new computer program for medical statistics.

In recent years, the use and abuse of statistics in the medical literature has extensively been reviewed. Amongst others, the importance of the P-value has been challenged and the use of misleading graphics, including 3-dimensional displays, has been criticized. The ease of access to more complex statistical procedures, since the introduction of several statistical software packages for personal computers, has been identified as one of the factors involved in the misuse of statistics. Therefore, we have developed a new computer program that includes those statistical procedures commonly encountered in the medical literature and in statistical textbooks for medical researchers. More complex statistical analyses are not implemented in the software. If researchers with limited statistical training require more sophisticated statistical analyses, they should refer to a statistician, not to a more complete statistical software package.

Computer Graphics↗
PubMed1990

Who should teach medical statistics, when, how and where should it be taught?

As far as we can tell, there is no single answer to any of these questions. This paper describes some of the approaches adopted in the teaching of medical statistics in the U.K. medical schools. It is suggested that collaboration between non-statistically qualified teachers and medical statisticians is beneficial, with an emphasis in the application of statistical principles to interesting and 'relevant' medical topics. A block of 'laboratory based' teaching in the early years may be followed by occasional, clinically focused sessions later in the undergraduate course. Research oriented courses, made available when postgraduates have a real and pressing need for information, are thought likely to be most valuable and rewarding for students and statisticians. It is thought that the use of information technology to improve the communication of concepts and 'facts' during lectures, and for ad hoc enquiries by students, is likely to make the most of the limited teaching resources. The future is thought to be in the greater use of small group or individualized teaching which confirms or tests the knowledge gained from students use of I.T. supported activities. Unless lecturers collaborate in evaluative studies which compare different teaching methods, it will never be possible to provide valid generalizable advice to teachers of medical statistics.

Education, Medical↗
PubMedDate not supplied

Theory and practice in medical statistics.

The discipline of statistics generally, and that of medical statistics in particular, has evolved through two traditions, the theoretical and the practical. Their history, traced briefly here, shows recurrent points of contact and a process of gradual merging which is now almost complete. However, the current tendency to build complex mathematical and computing models may lead to over-confidence in their conclusions, when some crucial aspects of the data cannot easily be modelled satisfactorily. Illustrations are drawn from the use of formal stopping rules in the monitoring of clinical trials, and from the treatment of missing data and incomplete compliance with the trial protocol.

Clinical Trials as Topic↗
PubMedDate not supplied

Support with clarity: a proper trend in medical statistics.

BACKGROUND: The aim of this study was to establish effective methods to review and evaluate, and to emphasize in support with clarity as a proper trend in medical statistics. METHODS: The clinical research material used in this study is stemmed from JAMC. STUDY: I, N is 220 subjects, from Pattern of Coronary Arterial Distribution and Its Relation to Coronary Artery Diameter, Z A Kaimkhani, MM Ali, AMA Faruqi JAMC Jan-Mar 2005; 17(1): 40-3. STUDY: II, N is 105 patients, from Sclerotherapy Plus Octreotide Versus Sclerotherapy Alone In The Management Of Gastro-Oesophageal Variceal Hemorrhage. HA Shah, K Mumtaz, W Jafri, S Abid, S Hamid, A Ahmad, Z Abbas. JAMC Jan-Mar 2005; 17(1): 10-4. 2 Systemic review and evaluation with statistical principles is to be used. ASSESSMENT AND DISCUSSION: The reports of 2 clinical researches from JAMC are assessed, and both used for demonstrating the characteristics and pitfalls statistically. CONCLUSION: Before reaching any significant difference in statistics, hopefully, all clinicians will be able to deal with the data to be measured by selecting proper statistical models as the best as we can in order to gain appropriate inference in medical statistics.

Humans↗
PubMed2000

Medical statistics--no time for complacency.

Statistical science plays an important role in medical research. Whether this will continue to be so, depends to a large extent on the future of fields like clinical trials and epidemiology. Will these continue to play the important role they do today in the development of medicine? Traditional, frequentist, methodology still dominates in medical statistics. Statisticians should have an open and pragmatic attitude towards new approaches. Survival analysis is a field of biostatistics that has been through considerable recent development. The need for further methodological development in this field is stressed. There is also need for connecting statistical work more intimately to biological knowledge than is the case today.

Biometry↗
PubMed2005

Some challenges for medical statistics.

A broad review is given of some of the issues facing medical statistics organized under the headings of measurement, design, analysis and interpretation.

Clinical Medicine↗
PubMedDate not supplied

Paradigms and pragmatism: approaches to medical statistics.

Until recently, the dominant philosophy of science was that due to Karl Popper, with its doctrine that the proper task of science was the formulation of hypotheses followed by attempts at refuting them. In spite of the close analogy with significance testing, these ideas do not fit well with the practice of medical statistics. The same can be said of the later philosophy of Thomas Kuhn, who maintains that science proceeds by way of revolutionary upheavals separated by periods of relatively pedestrian research which are governed by what Kuhn refers to as paradigms. Through there have been paradigm shifts in the history of statistics, a degree of continuity can also be discerned. A current paradigm shift is embodied in the spread of Bayesian ideas. It may be that a future paradigm will emphasise the pragmatic approach to statistics that is associated with the name of Daniel Schwartz.

Clinical Trials as Topic↗
PubMed2005

An introduction to medical statistics for health care professionals: basic statistical tests.

This article, the third and final article in the series, aims to give health care professionals (HCPs) a sound and helpful introduction to medical statistics (Thomas, 2004, 2005). A brief summary of the content of the previous articles is given in Table 1. The current article will cover the area of basic statistical tests with the aim of guiding HCPs to the correct test for a particular research question and dataset. The article will not go into great depth of the formal methods of calculation required for all the tests covered but I would suggest that the reader refer to standard textbooks (Jordan et al., 1998; Swinscow, 1998; Altman, 1994; Bland, 2000), the help sections of statistical packages (SPSS or Stata), or consult a statistician. For ease of reference within the article the tests have been grouped by the data type, i.e. numerical or categorical. Further separation within each data type has been carried out depending on the number of groups being compared, whether the groups are independent, the size of the sample, and, in the case of numerical data, the distribution of the variable. For quick reference, two other tables are also presented which summarize which analysis methods should be used in each situation.

Journal Article↗
PubMed1991

[An underestimated forerunner: Marc-Jacob D'Espine (1806-1860) and medical statistics].

This article relates the life and work of Marc-Jacob D'Espine, a disciple of P.C.A. Louis and a somewhat unrecognised predecessor of medical statistics. Many extracts of his unpublished correspondence are given. After a short biography, the scientific work of D'Espine as well as his action to diffuse his ideas--in Switzerland as well as in foreign countries--are discussed.

History, 19th Century↗
PubMed2005

An introduction to medical statistics for health care professionals: Hypothesis tests and estimation.

This article is the second in a series of three that will give health care professionals (HCPs) a sound introduction to medical statistics (Thomas, 2004). The objective of research is to find out about the population at large. However, it is generally not possible to study the whole of the population and research questions are addressed in an appropriate study sample. The next crucial step is then to use the information from the sample of individuals to make statements about the wider population of like individuals. This procedure of drawing conclusions about the population, based on study data, is known as inferential statistics. The findings from the study give us the best estimate of what is true for the relevant population, given the sample is representative of the population. It is important to consider how accurate this best estimate is, based on a single sample, when compared to the unknown population figure. Any difference between the observed sample result and the population characteristic is termed the sampling error. This article will cover the two main forms of statistical inference (hypothesis tests and estimation) along with issues that need to be addressed when considering the implications of the study results.

Journal Article↗
PubMed2006

'A memorandum on the Present Position and Prospects of Medical Statistics and Epidemiology' by Major Greenwood.

We present an unpublished, possibly unsent, memorandum written by Major Greenwood in 1928 that is of historical importance. It raises three issues, namely, the profile of medical statistics in 1928, the development of mathematical statistics in the U.K., and the staffing of his own department. Some of these issues are still relevant today. We discuss each of them against the historical background of the first quarter of the 20th century. Some additional biographical details relevant to the understanding of the memorandum are provided in an Appendix.

Epidemiology↗
PubMed1996

The statistical big bang of 1911: ideology, technological innovation and the production of medical statistics.

This paper examines the relationship between intellectual debate, technologies for analysing information, and the production of statistics in the General Register Office (GRO) in London in the early twentieth century. It argues that controversy between eugenicists and public health officials respecting the cause and effect of class-specific variations in fertility led to the introduction of questions in the 1911 census on marital fertility. The increasing complexity of the census necessitated a shift from manual to mechanised forms of data processing within the GRO. The subsequent increase in processing power allowed the GRO to make important changes to the medical and demographic statistics it published in the annual Reports of the Registrar General. These included substituting administrative sanitary districts for registration districts as units of analysis, consistently transferring deaths in institutions back to place of residence, and abstracting deaths according to the International List of Causes of Death.

Censuses↗
PubMed1999

Critical evaluation of medical, statistical, and occupational data sources in the Kola Peninsula of Russia pertinent to reproductive health studies.

BACKGROUND: The feasibility study described herein was prompted by a report in 1992 of possible reproductive and developmental health concerns among female workers in a Russian nickel refinery. OBJECTIVE: The primary goal was to ascertain whether medical, statistical, and occupational data bases could be accessed for information about the pregnancy histories, occupational histories, and life-style factors of the women affected. METHODS: The project was facilitated by construction of a registry of all births in three towns with a nickel refinery and verification of its contents against patients' records obtained from hospital delivery and gynecology departments and community polyclinics. Municipal Registration Board, Regional Health Statistics Board, and nickel company records were also reviewed. RESULTS: Reproductive/developmental outcome information and workplace histories were acceptable. Sample-size calculations indicated that a cohort or cross-sectional study would be amenable and suitable for the detection of an excess risk for spontaneous abortion with adequate statistical significance and power. Such investigations would need to be supplemented by workplace environmental/biological monitoring assessments for evaluation of exposure to occupational hazardous factors and a worker's questionnaire to obtain information about life-style factors. A case-control design is recommended for the study of congenital defects. CONCLUSIONS: A well-designed, comprehensive epidemiology study is technically feasible because of the availability of a favorable pool of study subjects, reproductive/developmental outcome data, information to control for major confounders, and suitable occupational records.

Adult↗
PubMed1985

Biometry and medical statistics.

The "biometric school" founded by K. Pearson, F. Galton, and W. F. R. Weldon was concerned especially with heredity and variation, and between the wars "biometry" was not widely used as a general term for quantitative biology. The foundation of the Biometric Society encouraged this wider usage, and medical and biological statistics were seen to share a common methodology. In recent years, medical statistics has developed more rapidly, and this growth has been reflected in the contents of Biometrics. The author stresses the essential unity of the subject, the central core of which is the application of statistics in the life sciences. The Society should encourage contact with those workers in quantitative biology who are outside this central tradition.

Biometry↗