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PubMed2002

The effect of dedicated methodology and statistical review on published manuscript quality.

STUDY OBJECTIVE: We examine how dedicated methodology and statistical review affects the quality of manuscripts published in Annals of Emergency Medicine. DESIGN: The dedicated reviewers developed a manuscript scoring form based on previously used instruments. The form contained 84 unique elements. Eight items sought the presence of state-of-the-art features (eg, formal exploration of the sensitivity of results to assumptions); the others sought substandard quality. Two raters independently scored each original research publication appearing in 4 consecutive issues of Annals for the presence or absence of each relevant item. We then reviewed the formal methodology and statistical review and all subsequent correspondence between authors and editors to determine whether the methodology and statistical review provided guidance regarding each of the 84 items and whether the advice was incorporated into the final manuscript. RESULTS: There were 32 original research articles. One was never subjected to methodology and statistical review. Reviewers agreed on 94% of all items; single-item agreement ranged from 77% to 100%. State-of-the-art features were present in 31 (14%) of 217 ratings; the methodology and statistical review had commented on 13 (42%) of these. State-of-the-art features were absent in 186 (86%) ratings; the methodology and statistical review had commented on 33 (18%) of these. Substandard features were deemed present in 166 (12%) of 1,519 ratings; the methodology and statistical review had commented on 82 (44%) of these. Substandard features were absent in 1,333 (88%) ratings; the methodology and statistical review had commented on 132 (10%) of these. We found no fatal flaws in the published manuscripts. CONCLUSION: Methodology reviewers often failed to comment on deficiencies that they had classified as substandard when designing this study. Reviews also did not encourage inclusion of state-of-the-art abstract, article, and references features. When reviews identified areas in need of improvement, only half of the comments led to improved manuscripts. In the other half, authors either rebuked the suggestions or the editors did not act when suggestions were ignored.

Peer Review, Research↗

PubMed2006

Changes in safety on England's roads: analysis of hospital statistics.

OBJECTIVE: To compare trends in the numbers of people with serious traffic injuries according to police statistics and hospital episode statistics (HES). DESIGN: Descriptive study based on two independent population based data sources. SETTING: Police statistics and hospital episode statistics in England. MAIN OUTCOME MEASURES: Rates of injury and death and their change over time reported in each data source, for 1996 to 2004. RESULTS: According to police statistics, rates of people killed or seriously injured on the roads fell consistently from 85.9 per 100,000 in 1996 to 59.4 per 100,000 in 2004. Over the same time, however, hospital admission rates for traffic injuries were almost unchanged at 90.0 in 1996 and 91.1 in 2004. Both datasets showed a significant reduction in rates of injury in children aged < or = 15, but the reduction in hospital admission rates was substantially less than the reduction shown in the police statistics. The definition of serious injury in police statistics includes every hospital admission; in each year, none the less, the number of admissions exceeded the number of injuries reported in the police system. CONCLUSIONS: The overall fall seen in police statistics for non-fatal road traffic injuries probably represents a fall in completeness of reporting of these injuries.

Accidents, Traffic↗

PubMed2000

Statistical methods in public health and epidemiology: a look at the recent past and projections for the next decade.

This article attempts to prognosticate from past patterns, the type of statistical methods that will be used in published public health and epidemiological studies in the decade that follows the millennium. With this in mind, we conducted a study that would characterize trends in use of statistical methods in two major public health journals: the American Journal of Public Health, and the American Journal of Epidemiology. We took a probability sample of 348 articles published in these journals between 1970 and 1998. For each article sampled, we abstracted information on the design of the study and the types of statistical methods used in the article. Our major findings are that the proportion of articles using statistical methods as well as the mean number of statistical methods used per article has increased dramatically over the three decades surveyed. Also, the proportion of published articles using study designs that we classified as analytic has increased over the years. We also examined patterns of use in these journals of three statistical methodologies: logistic regression, proportional hazards regression, and methods for analysis of data from complex sample surveys. These methods were selected because they had been introduced initially in the late 1960s or early 1970s and had made considerable impact on data analysis in the biomedical sciences in the 1970s-90s. Estimated usage of each of these techniques remained relatively low until user-friendly software became available. Our overall conclusions are that new statistical methods are developed on the basis of need, disseminated to potential users over a course of many years, and often do not reach maximum use until tools for their comfortable use are made readily available to potential users. Based on these conclusions, we identify certain needs that are not now being met and which are likely to generate new statistical methodologies that we will see in the next decade.

Biometry↗

PubMed2005

A flexibly shaped spatial scan statistic for detecting clusters.

BACKGROUND: The spatial scan statistic proposed by Kulldorff has been applied to a wide variety of epidemiological studies for cluster detection. This scan statistic, however, uses a circular window to define the potential cluster areas and thus has difficulty in correctly detecting actual noncircular clusters. A recent proposal by Duczmal and Assunção for detecting noncircular clusters is shown to detect a cluster of very irregular shape that is much larger than the true cluster in our experiences. METHODS: We propose a flexibly shaped spatial scan statistic that can detect irregular shaped clusters within relatively small neighborhoods of each region. The performance of the proposed spatial scan statistic is compared to that of Kulldorff's circular spatial scan statistic with Monte Carlo simulation by considering several circular and noncircular hot-spot cluster models. For comparison, we also propose a new bivariate power distribution classified by the number of regions detected as the most likely cluster and the number of hot-spot regions included in the most likely cluster. RESULTS: The circular spatial scan statistics shows a high level of accuracy in detecting circular clusters exactly. The proposed spatial scan statistic is shown to have good usual powers plus the ability to detect the noncircular hot-spot clusters more accurately than the circular one. CONCLUSION: The proposed spatial scan statistic is shown to work well for small to moderate cluster size, up to say 30. For larger cluster sizes, the method is not practically feasible and a more efficient algorithm is needed.

Journal Article↗

PubMed2006

Statistical methodologies in psychopharmacology: a review.

There has been a greatly increased interest in statistical methods in the psychiatric research and its applications over the past few decades, in parallel with advances in computers and statistical software. This review aims to describe the main topics related to statistical methods in psychopharmacology, namely nature of statistics in medicine, problems in data analysis, statistical modelling, developments in statistical technology, statistical reporting and meta-analysis.

Animals↗

PubMed1991

Thomas: building Bayesian statistical expert systems to aid in clinical decision making.

Knowledge-based system for classical statistical analysis must separate the task of analyzing data from that of using the results of the analysis. In contrast, a Bayesian framework for building biostatistical expert system allows for the integration of the data-analytic and decision-making tasks. The architecture of such a framework entails enabling the system (1) to make its recommendations on decision-analytic grounds; (2) to construct statistical models dynamically; (3) to update a statistical model based on the user's prior beliefs and on data from, the methodological concerns evinced by, the study. This architecture permits the knowledge engineer to represent a variety of types of statistical and domain knowledge. Construction of such systems requires that the knowledge engineer reinterpret traditional statistical concerns, such as by replacing the notion of statistical significance with that of a pragmatic clinical threshold. The clinical user of such a system can interact with the system at a semantic level appropriate to her fund of methodological knowledge, rather than at the level of statistical details. We demonstrate these issues with a prototype system called THOMAS which helps a physician decision maker interpret the results of a published randomized clinical trial.

Artificial Intelligence↗

PubMed2004

Understanding tuberculosis epidemiology using structured statistical models.

Molecular epidemiological studies can provide novel insights into the transmission of infectious diseases such as tuberculosis. Typically, risk factors for transmission are identified using traditional hypothesis-driven statistical methods such as logistic regression. However, limitations become apparent in these approaches as the scope of these studies expand to include additional epidemiological and bacterial genomic data. Here we examine the use of Bayesian models to analyze tuberculosis epidemiology. We begin by exploring the use of Bayesian networks (BNs) to identify the distribution of tuberculosis patient attributes (including demographic and clinical attributes). Using existing algorithms for constructing BNs from observational data, we learned a BN from data about tuberculosis patients collected in San Francisco from 1991 to 1999. We verified that the resulting probabilistic models did in fact capture known statistical relationships. Next, we examine the use of newly introduced methods for representing and automatically constructing probabilistic models in structured domains. We use statistical relational models (SRMs) to model distributions over relational domains. SRMs are ideally suited to richly structured epidemiological data. We use a data-driven method to construct a statistical relational model directly from data stored in a relational database. The resulting model reveals the relationships between variables in the data and describes their distribution. We applied this procedure to the data on tuberculosis patients in San Francisco from 1991 to 1999, their Mycobacterium tuberculosis strains, and data on contact investigations. The resulting statistical relational model corroborated previously reported findings and revealed several novel associations. These models illustrate the potential for this approach to reveal relationships within richly structured data that may not be apparent using conventional statistical approaches. We show that Bayesian methods, in particular statistical relational models, are an important tool for understanding infectious disease epidemiology.

Adult↗

PubMed2003

[Use of statistical analysis in original articles in "Actas Urológicas Españolas." Accessibility for the reader].

OBJECTIVES: To describe the use of statistical methods employed in original articles published in Actas Urológicas Españolas as the first step to quantify the accessability for the readers. METHODS: Observational, retrospective, descriptive and transversal study to analize all the original articles published in Actas Urológicas Españolas during the year 2000. Once the anectotic cases were excluded, 55 original studies were selected. In each article it was minuciously reviewed the methods and results sections, tables and figures included, to identify the statistical analysis used and to classify them into 18 categories with three accessability levels as Emerson and Colditz and Mora y cols, previously reported: descriptive statistics, bivariables analysis and complex analysis. A randomized sample of the originals were reviewed again by the same investigator three months later to evaluate the criteria liability. The accessability was defined as a) article dependent (rate of originals that readers with different statistical knowledge are able to understand) and b) analysis dependent (rate of statistical methods respect to the total performed overall the articles that readers are able to understand). RESULTS: Our major findings are that the more frequently used technics are descriptive analysis (39.3%), bivariable tables (12.1%), survival analysis (10%), t Student and z tests (6%), and nonparametric tests (8.6%). The accessability for a reader which statistical konowledge includes bivariable methods is 63.6% (IC 95% 49%-76%) and 79% (IC 95% 71%-85), article and analysis dependent respectively, rates that are similar to the reported for biomedical journals in our country. CONCLUSIONS: A great percentage of original articles in Actas Urológicas Españolas includes complex analysis. It could be good that readers were able to increase our statistical and methodological knowledge to perform a critical approach to our publication.

Bibliometrics↗

PubMed2004

Bias toward the null hypothesis in model-free linkage analysis is highly dependent on the test statistic used.

Recently, it has been suggested that traditional nonparametric multipoint-linkage procedures can show a "bias" toward the null hypothesis of no effect when there is incomplete information about allele sharing at genotyped marker loci (or at positions in between marker loci). Here, I investigate the extent of this bias for a variety of test statistics commonly used in qualitative- ("affecteds only") and quantitative-trait linkage analysis. Through simulation and analytical derivation, I show that many of the test statistics available in standard linkage analysis packages (such as Genehunter, Merlin, and Allegro) are, in fact, not affected by this bias problem. A few test statistics--most notably the nonparametric linkage statistic and, to a lesser extent, the Aspex-MLS and Haseman-Elston statistics--are affected by the bias. Variance-components procedures, although unbiased, can show inflation or deflation of the test statistic attributable to the inclusion of pairs with incomplete identity-by-descent information. Results obtained--for instance, in genome scans--using these methods might therefore be worth revisiting to see if greater power can be obtained by use of an alternative statistic or by eliminating or downweighting uninformative relative pairs.

Alleles↗

PubMed2003

Statistical significance analysis of longitudinal gene expression data.

MOTIVATION: Time-course microarray experiments are designed to study biological processes in a temporal fashion. Longitudinal gene expression data arise when biological samples taken from the same subject at different time points are used to measure the gene expression levels. It has been observed that the gene expression patterns of samples of a given tumor measured at different time points are likely to be much more similar to each other than are the expression patterns of tumor samples of the same type taken from different subjects. In statistics, this phenomenon is called the within-subject correlation of repeated measurements on the same subject, and the resulting data are called longitudinal data. It is well known in other applications that valid statistical analyses have to appropriately take account of the possible within-subject correlation in longitudinal data. RESULTS: We apply estimating equation techniques to construct a robust statistic, which is a variant of the robust Wald statistic and accounts for the potential within-subject correlation of longitudinal gene expression data, to detect genes with temporal changes in expression. We associate significance levels to the proposed statistic by either incorporating the idea of the significance analysis of microarrays method or using the mixture model method to identify significant genes. The utility of the statistic is demonstrated by applying it to an important study of osteoblast lineage-specific differentiation. Using simulated data, we also show pitfalls in drawing statistical inference when the within-subject correlation in longitudinal gene expression data is ignored.

Adaptation, Physiological↗

PubMed1999

Tools of the trade: statistical analysis in dermatopathology articles.

Statistical analysis of research results provides powerful tools for understanding the data from projects. A prospective review of the statistical methods utilized in 100 consecutive articles in the recent literature relevant to dermatopathology was performed. The majority of papers, 75%, did not contain statistical analyses. A wide variety of methods were utilized in the papers that did have statistical analyses including methods in the following categories: t-test, contingency tables, multiple regression, multiple comparisons, nonparametric tests, life tables, and survival tests. Nine of the 25 papers utilizing statistical analysis had problems in the methods. These problems included treating categorical data as a continuous variable, multiple comparisons, subgroup analysis, and discordance of statistics and conclusions. It is important to understand the underlying assumptions of statistical methods to use the appropriate tets. These are tools of the trade for dermatopathology investigators.

Data Interpretation, Statistical↗

PubMed2000

[Statistical considerations for preparation of a study report on pharmacological studies].

In order to develop a new drug with scientific rationale, it is important to collect and analyze data in accordance with the protocol and to report it correctly. We suggested appropriate statistical considerations with regards to the following five points for preparing a study report on a pharmacological study: 1. For describing statistical analysis, it is important to describe the applied statistical methods concretely; 2. For describing subjects included in the analysis, it is necessary to describe the number of subjects excluded from analysis along with the reasons for their exclusion, and it is important to describe the comparability among groups; 3. For preparation of tables and figures, it is necessary to prepare tables and figures with sufficient statistical information; 4. For proper expression of the results and a meaningful discussion, we suggested the importance of drawing pharmacological conclusions with sufficient knowledge of the applied statistical methods and also suggested the statistical considerations for utilizing information obtained from the results; 5. For compiling an integrated report from two or more study reports, we suggested statistical considerations for discussing the consolidated results. We expect researchers will be able to obtain more reliable conclusions by preparing a study report taking our suggestions into consideration.

Animals↗

PubMed2004

Statistical methods for detecting genomic alterations through array-based comparative genomic hybridization (CGH).

Array-based comparative genomic hybridization (ABCGH) is an emerging high-resolution and high-throughput molecular genetic technique that allows genome-wide screening for chromosome alterations associated with tumorigenesis. Like the cDNA microarrays, ABCGH uses two differentially labeled test and reference DNAs which are cohybridized to cloned genomic fragments immobilized on glass slides. The hybridized DNAs are then detected in two different fluorochromes, and the significant deviation from unity in the ratios of the digitized intensity values is indicative of copy-number differences between the test and reference genomes. Proper statistical analyses need to account for many sources of variation besides genuine differences between the two genomes. In particular, spatial correlations, the variable nature of the ratio variance and non-Normal distribution call for careful statistical modeling. We propose two new statistics, the standard t-statistic and its modification with variances smoothed along the genome, and two tests for each statistic, the standard t-test and a test based on the hybrid adaptive spline (HAS). Simulations indicate that the smoothed t-statistic always improves the performance over the standard t-statistic. The t-tests are more powerful in detecting isolated alterations while those based on HAS are more powerful in detecting a cluster of alterations. We apply the proposed methods to the identification of genomic alterations in endometrium in women with endometriosis.

Chromosome Aberrations↗

PubMed1998

Statistical analysis: the need, the concept, and the usage.

In general, better understanding of the need and usage of statistics would benefit the medical community in India. This paper explains why statistical analysis is needed, and what is the conceptual basis for it. Ophthalmic data are used as examples. The concept of sampling variation is explained to further corroborate the need for statistical analysis in medical research. Statistical estimation and testing of hypothesis which form the major components of statistical inference are construed. Commonly reported univariate and multivariate statistical tests are explained in order to equip the ophthalmologist with basic knowledge of statistics for better understanding of research data. It is felt that this understanding would facilitate well designed investigations ultimately leading to higher quality practice of ophthalmology in our country.

Data Interpretation, Statistical↗

PubMed1992

Statistical techniques in ophthalmic journals.

Over the years, the use of statistics to evaluate experimental data in ophthalmology has increased. The present study sought to assess the frequency and types of statistical techniques used in ophthalmic journals. We reviewed 974 original articles from the Archives for 1970, 1980, and 1990; the American Journal of Ophthalmology for 1990; and Ophthalmology for 1990. Of the 592 articles reviewed for 1990, 391 (66.0%) contained statistics, with measures of central tendency most commonly used (385 articles [65.0%]), followed by dispersion (298 [50.3%]), t test (120 [20.3%]), and contingency tables (98 [16.6%]). A reader familiar with 10 statistical techniques would have "statistical accessibility" to 526 (88.9%) of 1990 articles. A statistically significant difference was found in the percentage of articles containing statistical methods among the journals (P = .0003; Archives, 75.3%; Ophthalmology, 66.8%; and American Journal of Ophthalmology, 55.2%).

Animals↗

PubMed1999

Does environmental data collection need statistics?

The term 'statistics' with reference to environmental science and policymaking might mean different things: the development of statistical methodology, the methodology developed by statisticians to interpret and analyse such data, or the statistical data that are needed to understand environmental pollution and to identify possible policy options. This may and indeed has led to confusion on the part of the users of 'statistics' in environmental science and policymaking. This paper focuses on some of the needs of environmental scientists for statistical methodologies to help us do our jobs better. Statisticians and statistics can contribute to environmental science and the environmental policymaking process in three main ways. First, in describing phenomena: this may in some cases be a non-trivial application of statistical methods. Second, by assessing causal relations: (multivariate) analysis techniques can be applied in establishing the (causal) relations between pressures, state and impact. Third, by setting and checking of standards: uncertainties between the dose-effect relations and the formulation of the standard, and the standard and the state of the environment should be carefully dealt with. Statisticians may help in formulating the standards in such a way that standard checking is as straightforward as possible.

Data Collection↗

PubMed2003

Sum statistics for the joint detection of multiple disease loci in case-control association studies with SNP markers.

In complex traits, multiple disease loci presumably interact to produce the disease. For this reason, even with high-resolution single nucleotide polymorphism (SNP) marker maps, it has been difficult to map susceptibility loci by conventional locus-by-locus methods. Fine mapping strategies are needed that allow for the simultaneous detection of interacting disease loci while handling large numbers of densely spaced markers. For this purpose, sum statistics were recently proposed as a first-stage analysis method for case-control association studies with SNPs. Via sums of single-marker statistics, information over multiple disease-associated markers is combined and, with a global significance value alpha, a small set of "interesting" markers is selected for further analysis. Here, the statistical properties of such approaches are examined by computer simulation. It is shown that sum statistics can often be successfully applied when marker-by-marker approaches fail to detect association. Compared with Bonferroni or False Discovery Rate (FDR) procedures, sum statistics have greater power, and more disease loci can be detected. However, in studies with tightly linked markers, simple sum statistics can be suboptimal, since the intermarker correlation is ignored. A method is presented that takes the correlation structure among marker loci into account when marker statistics are combined.

Algorithms↗

PubMed2005

QTL mapping with discordant and concordant sibling pairs: new statistics and new design strategies.

The term "extreme discordant and concordant" (EDAC) sampling has been used to describe a variety of strategies for quantitative trait locus mapping using sibling pairs sampled from the corners of the bivariate trait distribution. The principle of the design is to gain efficiency by genotyping only the most informative of the available sibling pairs. EDAC-type designs have been studied in a number of papers, and have been applied in a few others. This literature is somewhat out of date, however, because there are many new statistics that are appropriate for EDAC data. With newer statistics, the power of EDAC designs can be improved. Moreover, the relative power of different designs must be re-evaluated, because the newer statistics improve the power of some designs more than others. That is, there is a circular relationship between design and statistic choices. In this report, we review a number of available design and statistic choices for EDAC studies, and use simulation to show what statistics are most powerful for each design. We then use those more powerful statistics to suggest strategies for making design choices among various EDAC and non-EDAC designs that use sibling pairs. We find that when genotyping must be minimized, an EDAC design with predominantly discordant pairs is the best choice, and when a balance of genotyping and phenotyping effort must be achieved, single proband ascertainment can do better. We also show that moderately selected samples (as opposed to very extreme samples) can be an efficient choice for many studies.

Algorithms↗