[Statistics. Cancer mortality according to the mortality statistics of causes of death from the central bureau of statistics].
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Improved statistical inference from DNA microarray data using analysis of variance and a Bayesian statistical framework. Analysis of global gene expression in Escherichia coli K12.
We describe statistical methods based on the t test that can be conveniently used on high density array data to test for statistically significant differences between treatments. These t tests employ either the observed variance among replicates within treatments or a Bayesian estimate of the variance among replicates within treatments based on a prior estimate obtained from a local estimate of the standard deviation. The Bayesian prior allows statistical inference to be made from microarray data even when experiments are only replicated at nominal levels. We apply these new statistical tests to a data set that examined differential gene expression patterns in IHF(+) and IHF(-) Escherichia coli cells (Arfin, S. M., Long, A. D., Ito, E. T., Tolleri, L., Riehle, M. M., Paegle, E. S., and Hatfield, G. W. (2000) J. Biol. Chem. 275, 29672-29684). These analyses identify a more biologically reasonable set of candidate genes than those identified using statistical tests not incorporating a Bayesian prior. We also show that statistical tests based on analysis of variance and a Bayesian prior identify genes that are up- or down-regulated following an experimental manipulation more reliably than approaches based only on a t test or fold change. All the described tests are implemented in a simple-to-use web interface called Cyber-T that is located on the University of California at Irvine genomics web site.
Bayes Theorem↗
Can census offices publish statistics for more than one small area geography? An analysis of the differencing problem in statistical disclosure.
"The paper describes a problem faced by National Statistical Offices when publishing the results of decennial censuses for small geographical areas. If they publish statistical tables for two or more sets of areas, users can compare the tables and produce new statistics for the areas formed by differencing, which may have populations below confidentiality thresholds. To investigate the problem, the authors construct a software system and carry out a series of experiments using a large synthetic population base for Yorkshire and Humberside [in England]. The results indicate that publishing statistics for zones close in size to the primary areas is not safe unless the zones have been carefully designed. However, publishing statistics for sufficiently large areas such as 5km grid squares or postal sectors alongside enumeration districts is safe."
Censuses↗
Statistical significance versus clinical relevance. Part I. The essential role of the power of a statistical test.
When comparing two treatment groups, hypothesis testing is widely used. However, clinical trialists should be more interested in statistical methods which elicit the magnitude of the differences between treatment groups, rather than a simple indication of whether or not the differences are statistically significant. Statistical significance does not necessarily imply clinical relevance. If the true difference between two treatment groups is so small that it is clinically irrelevant, a sample size can be found for which this difference is statistically significant. On the other hand, if the difference between treatment groups is statistically non-significant, it may still be clinically important. The limitations of conventional hypothesis testing of equal true means as such are highlighted. The need to control the power of the test--which takes into account the difference in treatment means which is considered important (clinically relevant) by the researcher--is discussed.
Clinical Trials as Topic↗
Statistical learning in a serial reaction time task: access to separable statistical cues by individual learners.
The ability of adult learners to exploit the joint and conditional probabilities in a serial reaction time task containing both deterministic and probabilistic information was investigated. Learners used the statistical information embedded in a continuous input stream to improve their performance for certain transitions by simultaneously exploiting differences in the predictability of 2 or more underlying statistics. Analysis of individual learners revealed that although most acquired the underlying statistical structure veridically, others used an alternate strategy that was partially predictive of the sequences. The findings show that learners possess a robust learning device well suited to exploiting the relative predictability of more than I source of statistical information at the same time. This work expands on previous studies of statistical learning, as well as studies of artificial grammar learning and implicit sequence learning.
Adult↗
An examination of graduate students' statistical judgments: statistical and fuzzy set approaches.
The present study examined how statistical significance levels are treated and interpreted by graduate students who use hypothesis-testing in their scientific investigation. To test underlying psychological aspects of hypothesis-testing, the idea of fuzzy set theory was employed to identify the uncertain points in judgments. 34 graduate students in a psychology department made judgments about hypothetical statistical decisions. The results indicated that (1) the majority of these students treated significance levels on a continuum and rated them according to the magnitude of statistical significance; (2) the subjects shifted their decisions based on the types of hypothetical scenarios but not by the sample sizes; instead, they interpreted a smaller sample size as being less reliable. (3) The subjects frequently chose formally used statistical terms, e.g., Significant and Not Significant, more than graduated verbal expressions, e.g., Marginally Significant and Borderline Significant; and (4) the Fuzziness (degree of confidence in decision-making) was dependent on individuals and existed more in the critical points of transition where judgments are most difficult. The Fuzziness Index illustrated the subtle shifts of human decision-making patterns in statistical judgments. Underlying decision uncertainties and difficulties can be illustrated by functions generated from fuzzy set theory, which may more closely resemble human psychological mechanism. This integrative study of fuzzy set theory and behavioral measurements appears to provide a technique that is more natural for examining and understanding imprecise boundaries of human decisions.
Adult↗
Analysis of surveillance data: a rationale for statistical tests with comments on confidence intervals and statistical models.
In the examination of differences between subgroups in surveillance data, whether through simple counting or through sophisticated statistical modelling, the comparison is not between simple random samples from two or more populations. The rationale for statistical tests rests on an appeal to a model of random permutation of demographic and disease factors for the observed population during the surveillance period. The testing evaluates chance as a possible explanation for the observed results. In the analysis of internal structure in a surveillance data set, statistical tests produce a conceptually simple result that lends itself to concise presentation and flexible interpretation. Tests limit emphasis on probabilistic manipulation and on parameter estimates. They cannot stand alone, and thus encourage descriptive presentation of observations. In contrast, statistical models and confidence intervals emphasize parameters rather than distributions and compete with the data for limited space.
Data Interpretation, Statistical↗
Recommendations for statistical designs of in vivo mutagenicity tests with regard to subsequent statistical analysis.
A workshop was held on September 13 and 14, 1993, at the GSF, Neuherberg, Germany, to start a discussion of experimental design and statistical analysis issues for three in vivo mutagenicity test systems, the micronucleus test in mouse bone marrow/peripheral blood, the chromosomal aberration tests in mouse bone marrow/differentiating spermatogonia, and the mouse dominant lethal test. The discussion has now come to conclusions which we would like to make generally known. Rather than dwell upon specific statistical tests which could be used for data analysis, serious consideration was given to test design. However, the test design, its power of detecting a given increase of adverse effects and the test statistics are interrelated. Detailed analyses of historical negative control data led to important recommendations for each test system. Concerning the statistical sensitivity parameters, a type I error of 0.05 (one tailed), a type II error of 0.20 and a dose related increase of twice the background (negative control) frequencies were generally adopted. It was recommended that sufficient observations (cells, implants) be planned for each analysis unit (animal) so that at least one adverse outcome (micronucleus, aberrant cell, dead implant) would likely be observed. The treated animal was the smallest unit of analysis allowed. On the basis of these general consideration the sample size was determined for each of the three assays. A minimum of 2000 immature erythrocytes/animal should be scored for micronuclei from each of at least 4 animals in each comparison group in the micronucleus assays. A minimum of 200 cells should be scored for chromosomal aberrations from each of at least 5 animals in each comparison group in the aberration assays. In the dominant lethal test, a minimum of 400 implants (40-50 pregnant females) are required per dose group for each mating period. The analysis unit for the dominant lethal test would be the treated male unless the background frequency of dead implants (DI) is so low that multiple males would need to be integrated to meet the minimum observation of one adverse outcome (DI) per analysis unit. A three-step strategy of data analysis was proposed for the cytogenetic assays. Use of negative historical controls was allowed in certain circumstances for interpretation of results from micronucleus tests and chromosomal aberration tests.
Animals↗
Looking for statistical stability: a new method of evaluating reliability of statistical tests.
A new method of looking for statistical reliability, stability calculation, is described and is applied to statistical tests. Alike the power of statistical tests, stability calculation enables us to assess reliability of the latter. It belongs to the category of subsampling techniques that require using subsamples taken from the original sample. It provides descriptive and non-inferential results indicating the stability percentage: the percentage of sample elements to be removed, in order to change results obtained with the original sample. The higher is the stability percentage the more reliable is the statistical test. Stability percentage and power are correlated. Stability calculation provides informations about the elements in the sample, the most powerful points.
Computer Simulation↗
Statistical quality control methods in infection control and hospital epidemiology, Part II: Chart use, statistical properties, and research issues.
This is the second in a two-part series discussing and illustrating the application of statistical process control (SPC) in hospital epidemiology. The basic philosophical and theoretical foundations of statistical quality control and their relation to epidemiology are emphasized in order to expand the mutual understanding and cross-fertilization between these two disciplines. Part I provided an overview of the philosophy and general approach of SPC, illustrated common types of control charts, and provided references for further information or statistical formulae. Part II now discusses alternate possible SPC approaches, statistical properties of control charts, chart-design issues and optimal control limit widths, some common misunderstandings, and more advanced issues. The focus of both articles is mostly nonmathematical, emphasizing important concepts and practical examples rather than academic theory and exhaustive calculations.
Data Display↗
Methodological and statistical techniques: what do residents really need to know about statistics?
The purpose of this study was to catalog the statistical methods used in six journals two each from the fields of Family Practice, Emergency Medicine, and Obstetrics and Gynecology. We reviewed the quantitative articles from January 1998 through December 2000 from the Journal of Family Practice, the Journal of Family Medicine, the Annals of Emergency Medicine, the Journal of Academic Emergency Medicine. Articles from January 2000 through December 2000 of Obstetrics and Gynecology and the American Journal of Obstetrics and Gynecology were also included. Case reports and editorials were not included in this analysis. There were a total of 1828 articles reviewed (666 from Emergency Medicine articles, 380 from Family Practice, and 782 from Obstetrics and Gynecology). The distribution of study types (cross-sectional or survey, retrospective, or prospective) did not differ between the selected journals within Emergency Medicine, Family Practice, or Obstetrics and Gynecology. Pearson's chi-square/Fisher's Exact test was the statistic of choice overall (47.5%) followed by Student's t-test (33.1%). Analysis-of-variance was used in 23.3% of the studies, nonparametric methods (8.1%), linear regression (17.6%), and odds ratios/logistic regression (17.4%). Other statistical procedures were used less than 10% of the time. These results show that a physician who comfortably comprehends the appropriate use of descriptive statistics Student's t-test, Pearson's chi-square/Fisher's Exact test will be able to read and interpret at least 70% of the published medical literature. Educational efforts should focus on appropriate study design and analysis.
Clinical Competence↗
Statistical limitations in functional neuroimaging. I. Non-inferential methods and statistical models.
Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference.
Bayes Theorem↗
Survey of cause-of-death query criteria used by state vital statistics programs in the US and the efficacy of the criteria used by the Oregon Vital Statistics Program.
A survey of the 52 vital statistics registration areas in the United States revealed that at least 23 did not fulfill the minimum cause-of-death query guidelines recommended by the National Center for Health Statistics. The Oregon Center for Health Statistics is one of only a few that query certifying physicians at a comprehensive level. During August 1986-July 1987, a total of 2,453 of 23,238 death certificates were returned to the certifiers for additional information, not including those returned in a tobacco use study. More than one-half (56.1 per cent) resulted in new and more specific underlying cause-of-death data. Only 5.2 per cent of the queries were unanswered. One probable result of Oregon's program is that the state has the highest percentage of liver cirrhosis and disease deaths attributed to alcohol abuse in the United States. Nationally, 41.7 per cent of all liver disease and cirrhosis deaths in 1984 were listed as due to alcohol compared to 82.4 per cent in Oregon. The state's total liver cirrhosis and disease death rate (12.0 per 100,000 population) is only marginally higher than the United States rate (11.6). The query program also serves to locate maternal deaths that would otherwise not be reported, as well as to provide more accurate cause-of-death statistics in general.
Cause of Death↗
Statistical tests (Part 1): Descriptive statistics.
This series of three articles has been designed to facilitate an understanding of some commonly used statistical terms encountered when reading research articles. In addition, it is hoped that the nurse researcher who has access to a personal computer containing basic statistical software will gain some insight into which statistical tests to use and in what circumstances. The articles do not attempt to provide any understanding of the mathematics of the statistical tests employed.
Humans↗
Saving statistical lives: contributions of statistics to public health.
Prevention is about saving "statistical lives"-lives that society knows about only through the efforts of public health statisticians like Jack Smith. As Mr. Smith's lifework suggests, statistics in public health are critical for calling attention to problems, identifying risk factors, and suggesting solutions, and ultimately for taking credit for our successes. His work illustrates two important lessons about public health statistics today.First, it's important to get the facts straight. Mr. Smith's experience shows that a careful, thoughtful analysis is not only more convincing in the end, but also brings to light important subtleties not seen in the initial analysis. Second, it takes considerable time and attention to get the facts straight. Jack Smith's work illustrates the importance of partnerships with other federal agencies, state statistical organizations, and private-sector entities.
Biometry↗
Wave function statistics for ballistic quantum transport through chaotic open billiards: statistical crossover and coexistence of regular and chaotic waves.
For ballistic transport through chaotic open billiards, we implement accurate fully quantal calculations of the probability distributions and spatial correlations of the local densities of single-electron wave functions within the cavity. We find wave-statistical behaviors intrinsically different from those in their closed counterparts. Chaotic-scattering wave functions in open systems can be quantitatively interpreted in terms of statistically independent real and imaginary random fields in the same way as for wave-function statistics of closed systems in the time-reversal symmetry-breaking crossover regime. We also discuss perceived statistical deviations, which are attributed to the coexistence of regular and chaotic waves and given analytical explanations.
Journal Article↗
Application of statistics and frequency of statistical errors in articles in acta neurochirurgica.
Out of 395 contributions in the volumes 51 to 64 of Acta Neurochirurgica 141 reported numerical data. The frequency of procedures used for describing distribution, location or variability and the frequency of analytical methods were evaluated. Critical assessment of these articles revealed a considerable rate of fundamental errors in application of statistics. Considering only papers involving analytical methods 52% of these (33 out of 64) contained simple statistical errors which can be avoided without any statistician's help. Some rules for improving statistical quality of medical articles are presented.
Humans↗
Statistical issues in the analysis of the long-term carcinogenicity bioassay in small rodents: an empirical evaluation of statistical decision rules.
Data on 49 randomly selected studies from the NCI/NTP Carcinogenesis Bioassay Program were reanalyzed using four statistical decision rules to classify substances as either being negative or falling into one of three categories indicating increasing evidence of oncogenicity. The data available for analysis were the crude marginal counts of numbers of animals with specified lesions, as well as the number of animals surviving at the time the studies were terminated. Statistical analysis was based primarily on the Cochran-Armitage test for linear trend in proportions, with and without the use of historical control information. If only concurrent controls were used, classifications of carcinogenicity obtained in between 34 and 57% of the studies, depending on the decision rule used. The incorporation of historical control information into the Cochran-Armitage test statistic led to almost universal findings of carcinogenicity. The data base assembled here was used to estimate false negative and false positive rates for each of the four decision rules.
Animals↗