Statistical methodology in oral and dental research: pitfalls and recommendations. 2013

Ailish Hannigan, and Christopher D Lynch
Biomedical Statistics, Graduate Entry Medical School, University of Limerick, Limerick, Ireland. ailish.hannigan@ul.ie

OBJECTIVE This study describes the pitfalls for commonly used statistical techniques in dental research and gives some recommendations for avoiding them. It also explores the potential of some of the newer statistical techniques for dental research. METHODS Each of the commonly used techniques e.g. descriptive statistics, correlation and regression, hypothesis tests (parametric and non-parametric) and survival analysis are explored with examples and recommendations for their use are provided. Common sources of error including those of study design, insufficient information, ignoring the impact of clustering and underuse of confidence intervals are outlined. The potential of statistical techniques such as multivariate survival models, generalized estimating equations and multilevel models are also explored. CONCLUSIONS Reviews of published dental research repeatedly identify statistical errors in the design, analysis and conclusions of the study. Educating researchers on common pitfalls and giving recommendations for avoiding them may help researchers to eliminate statistical errors. Developments in statistical methodology should be routinely monitored to ensure the most appropriate statistical methods are used in dental research.

UI MeSH Term Description Entries
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D012107 Research Design A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly. Experimental Design,Data Adjustment,Data Reporting,Design, Experimental,Designs, Experimental,Error Sources,Experimental Designs,Matched Groups,Methodology, Research,Problem Formulation,Research Methodology,Research Proposal,Research Strategy,Research Technics,Research Techniques,Scoring Methods,Adjustment, Data,Adjustments, Data,Data Adjustments,Design, Research,Designs, Research,Error Source,Formulation, Problem,Formulations, Problem,Group, Matched,Groups, Matched,Matched Group,Method, Scoring,Methods, Scoring,Problem Formulations,Proposal, Research,Proposals, Research,Reporting, Data,Research Designs,Research Proposals,Research Strategies,Research Technic,Research Technique,Scoring Method,Source, Error,Sources, Error,Strategies, Research,Strategy, Research,Technic, Research,Technics, Research,Technique, Research,Techniques, Research
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D015999 Multivariate Analysis A set of techniques used when variation in several variables are studied simultaneously. In statistics, multivariate analysis is interpreted as any analytic method that allows simultaneous study of two or more dependent variables. Analysis, Multivariate,Multivariate Analyses
D016000 Cluster Analysis A set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both. Clustering,Analyses, Cluster,Analysis, Cluster,Cluster Analyses,Clusterings
D016001 Confidence Intervals A range of values for a variable of interest, e.g., a rate, constructed so that this range has a specified probability of including the true value of the variable. Confidence Interval,Interval, Confidence,Intervals, Confidence
D016019 Survival Analysis A class of statistical procedures for estimating the survival function (function of time, starting with a population 100% well at a given time and providing the percentage of the population still well at later times). The survival analysis is then used for making inferences about the effects of treatments, prognostic factors, exposures, and other covariates on the function. Analysis, Survival,Analyses, Survival,Survival Analyses
D018709 Statistics, Nonparametric A class of statistical methods applicable to a large set of probability distributions used to test for correlation, location, independence, etc. In most nonparametric statistical tests, the original scores or observations are replaced by another variable containing less information. An important class of nonparametric tests employs the ordinal properties of the data. Another class of tests uses information about whether an observation is above or below some fixed value such as the median, and a third class is based on the frequency of the occurrence of runs in the data. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed, p1284; Corsini, Concise Encyclopedia of Psychology, 1987, p764-5) Kolmogorov-Smirnov Test,Kruskal-Wallis H Statistic,Mann-Whitney U Test,Rank-Sum Tests,Spearman Rank Correlation Coefficient,Wilcox Test,Wilcoxon Rank Test,Non-Parametric Statistics,Nonparametric Statistics,Statistics, Non-Parametric,Kolmogorov Smirnov Test,Mann Whitney U Test,Non Parametric Statistics,Rank Sum Tests,Rank Test, Wilcoxon,Rank-Sum Test,Statistics, Non Parametric,Test, Kolmogorov-Smirnov,Test, Mann-Whitney U,Test, Rank-Sum,Test, Wilcox,Test, Wilcoxon Rank,Tests, Rank-Sum,U Test, Mann-Whitney
D018865 Dental Research The study of laws, theories, and hypotheses through a systematic examination of pertinent facts and their interpretation in the field of dentistry. (From Jablonski, Illustrated Dictionary of Dentistry, 1982, p674) Research, Dental

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