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Archive organized by category (July 7, 2006)

(Update: June 2007) I'm still updating and simplifying the topic list. This page, however, has grown so big that I need to split it into individual pages for each topic. This task is partially complete, and those pages still needing attention are marked as "[incomplete]". I am also including a brief description of each category and organizing categories into common themes.

Here are the themes (five so far, I may add a few more).

  • Theme: Data analysis. These categories cover a variety of methods for analyzing data from simple statistics to complex models.
  • Theme: Details about these webpages and their author. These categories cover details from my professional life as well as information on the website itself.
  • Theme: Disseminating research results. These categories cover information about how to present research findings effectively.
  • Theme: Evidence based medicine. These categories cover the major steps in evidence based medicine (asking a question, finding appropriate information, reviewing the quality of evidence, and applying the results to your particular practice. I place special emphasis on those aspects of evidence based medicine that relate to the practice of statistics.
  • Theme: Planning a research study. This theme covers important issues in the development of a research study, such as ethical concerns, justification of the sample size, and designing a survey.
  • Theme: Outside resources. This theme includes a variety of resources outside of the StATS webpages that I use and encourage others to use.

A chronological list of entries is available for the years 2007, 2006, 2005, and 2004.

Here are the new categories:

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

A

Category: Accrual problems in clinical trials. These pages cover some of the issues associated with accrual problems, research studies that accrue patients too slowly.

Category: Adverse events in clinical trials. These pages discuss methods for monitoring the frequency of adverse events in a clinical trial or safety study.

Category: Analysis of means. Analysis of means (ANOM) is an approach used in quality control circles to compare averages, proportions, or counts across several groups.

Category: Analysis of variance. Analysis of variance (ANOVA) is an approach that allows you to compare a continuous outcome variable across a factor representing three or more groups and to examine interactions among factors.

Category: Ask Professor Mean. Get answers to your Statistics questions from Professor Mean. He's not your average professor!

B

Category: Bayesian statistics. In Bayesian statistics, the researcher specifies a probability distribution prior to the start of the experiment that represents his/her degree of belief about the possible values of a process being studied. After data is collected, the Bayesian analysis produces a posterior distribution that combines information from data with information from the prior distribution.

Category: Blinding in research. Blinding is the process in a research study of hiding information about which treatment a patient receives.

C

Category: Children in research. Research in children raises special considerations in ethics, medicine, and statistics.

Category: Clinical importance. Clinical importance represents a change or shift in the outcome between the treatment group and the control group that is large enough to have a practical impact on the patient.

Category: Confidence intervals. A confidence interval provides a range of plausible values for an estimate that accounts for sampling error.

Category: Conflict of interest. Conflict of interest represents an outside influence, usually financial, that has the potential to upset the balance of impartiality that is important in credible research.

Category: Control charts. A control chart is a graphical tool used in many industrial settings that monitors a work process on a continual and on-going basis.

Category: Corroborating evidence. Corroborating evidence is information from outside the research study that supplements and strengthens the persuasiveness of a research finding.

Category: Covariate adjustment. Covariate adjustment is the use statistical methods (most notably analysis of covariance or ANCOVA) to correct for an imbalance in an important prognostic variable between a treatment/exposure group and a control group.

Category: Critical appraisal. Critical appraisal is the ability to judge the persuasiveness of the evidence in a research study. You have to strike the proper balance between being too harsh and being too accepting of research findings.

D

Category: Data management. Data management is the foundation of every good data analysis. You need to consider issues like how your data are entered, documented, and stored. Careful attention to these issues now will help save you time and frustration during your data analysis.

Category: Data mining. Data mining is a broad class of statistical tools that are designed for massive data sets. Many of the links in this category refer to methods for genetic data sets, especially microarray studies.

Category: Definitions. This page lists brief definitions of commonly used terms in statistics and research.

Category: Descriptive statistics. Descriptive statistics are statistics that are not used to test a formal research hypothesis, but rather to describe general features of a data set. I also use this category to represent very simple and fundamental issues in data analysis.

Category: Diagnostic Testing. Evaluation of diagnostic tests involves some subtle but important issues in Statistics. These webpages show some interesting examples of diagnostic tests, offer pointers for critical evaluation of studies of diagnostic tests, and present practical applications of diagnostic tests in your day-to-day medical practice.

E

Category: Early stopping in clinical trials. Clinical trials are sometimes stopped because of early evidence of efficacy, early evidence of harm, or early evidence of futility. In general, the rules for stopping a study need to be specified in the research protocol before any data is collected. These pages discuss some of the issues associated with early stopping of clinical trials.

Category: Equipoise in research. In a study where you randomly assign patients to two or more different treatments, you need to provide assurance that none of the patients is being harmed by having a chance at receiving an inferior therapy. This assurance has several different definitions coming from several different research perspectives, but a commonly used term is "equipoise". These pages discuss some of the ethical and practical issues associated with equipoise as well as debate over the proper interpretation of this and other closely related terms.

Category: Ethics in research. These pages describe some of the ethical principles in the conduct of research as well as information on how an Institutional Review Board (IRB) or other research ethics board evaluates research proposals.

Category: Exclusions in research. These pages discuss the problems with generalizability that occur when researchers include important segments of the population from their research or when research subjects refuse to participate.

Category: Extrapolations in research. These pages discuss some of the issues that you should consider when evaluating whether it is appropriate to extrapolate research finding to a different group of patients or to a different practice.

F

Category: Fraud in research. These pages discuss recent examples of fraudulent research, false allegations of fraud, and the research community's efforts to reduce or eliminate fraud.

G

Category: Grant writing. These pages offer some practical advice I have found on how to write an effective grant.

Category: Graphical display. These links discuss some of the issues that you need to consider when displaying research data using a graph.

H

Category: Human side to statistics. Although statistics involves numbers and formulas, it also involves human interactions. You provide statistical analysis in the context of a team effort to examine a research question, and this means that you need to be aware of human issues in the production of statistics.

Category: Hypothesis testing. Hypothesis testing is a set of formal methods to select between two competing research hypotheses. These pages discuss some of the philosophical underpinnings for hypothesis testing as well as some pragmatic concerns.

I

Category: Information searching. These pages describe efficient strategies for finding information in peer-reviewed journals or on the Internet.

Category: Information theory. These pages describe information theory, a branch of mathematics developed by Claude Shannon in the 1940's to model signals going through telephone lines. Information theory has found a diverse range of applications in areas like file compression and genetics.

Category: Interesting articles. This category lists interesting articles that I have mentioned on my weblog. Most of these articles are in peer-reviewed journals. I list links to full text and/or PDFs when they are available.

Category: Interesting books. These links present books that I have found useful and general information about writing books.

Category: Interesting quotes. These pages present interesting quotes that I have found. Almost all of these quotes relate to the practice of statistics. I try to acknowledge the resource (such as a web compilation of famous quotes) when I can.

Category: Interesting stuff. These pages list interesting websites, publications, and quotes that I have accumulated in my weblog. I hope to move some of the to pages on Interesting websites and Interesting articles as well as provide a brief annotation or excerpt from each resource.

Category: Interesting websites. This category includes a wide range of websites that I have highlighted in my weblog. I have included a brief annotation for recent entries, and will try to add annotations to earlier entries when I have time.

J

K

L

Category: Linear regression. The linear regression model provides a framework for quantitative predictions of an outcome variable that is continuous, using one or more predictor variables.

Category: Logistic regression. The logistic regression model provides a framework for quantitative predictions of an outcome variable that is categorical, using one or more predictor variables.

M

Category: Measuring agreement (includes validity/reliability). There are several ways to calculate the degree of agreement between two variables that are purporting to measure the same thing. In addition to describing these measures, this category includes discussion of assessment of reliability and validity, which is typically done by establishing a strong degree of agreement.

Category: Measuring benefit/risk. There are many measures of risk or benefit. I describe some of these (the odds ratio, the relative risk, the number needed to treat) and explain the advantages and disadvantages of particular measures.

Category: Mixed linear regression models. Mixed linear regression models, also known as random coefficient models extend the simple linear regression model to cases where you have to characterize variation between patients and within patients.

Category: Modeling issues. These pages discuss issues about statistical models which are relevant across a broad class of models. These pages may mention a specific model like logistic regression to provide context, but the ideas generalize easily to other models.

Category: Multiple comparisons. The use of multiple statistical tests in a wide range of contexts, raises serious concerns. The proposed solutions to these concerns are very controversial. These pages discuss some of the concerns and the debate over the appropriate remedies.

N

Category: Nonlinear regression. These pages describe regression models where you specify a nonlinear functional relationship.

O

Category: Observational studies. Observational studies are studies where the experimenter does not choose who gets into the control group and the treatment/exposure group. Rather the patients and/or their physicians make this choice, or the groups were intact prior to the start of the research. Observational studies raise some important methodological challenges, but when they are used carefully, they provide valuable insights that are not possible with other research designs.

P

Category: Pilot studies. Pilot studies are research studies which derive no direct benefit, but rather which provide benefit through assisting with the planning of a future research study. These pages present some of the issues associated with running a pilot study.

Category: Placebo controlled trials. A placebo is an inert substance that looks and tastes like an active drug, which is used in research studies to provide a blinded comparison group for the active drug. In a study of a medical device or a physical intervention, the placebo takes a different form. Placebo controlled trials raise difficult ethical and logistical concerns.

Category: Poisson regression. Poisson regression is quite simply a regression model that assumes that the outcome variable follows a Poisson distribution. These regression models are commonly used to predict count or rate variables. These pages describe how Poisson regression works and some of the issues associated with these models.

Category: Post hoc power. Post hoc power represents a calculation of power after the data have been collected. These pages explain why this calculation is not appropriate.

Category: Presenting research data. These pages present information about how to explain your research in a presentation or in a publication.

Category: Privacy in research. These pages discuss the special ethical considerations for research studies that involve the use of private and sensitive information.

Category: Probability concepts. These pages discuss some of the practical and theoretical considerations concerning probability.

Category: Professional details. These pages explain new developments in my professional career.

Category: Publication bias. Publication bias is the tendency for researchers who have data with a negative conclusion to fail to publish their work. These pages discuss the problems that publication bias causes, especially for those researchers who are performing a systematic overview.

Category: Pvalues. A p-value is a measure of evidence commonly used in hypothesis testing. These pages describe some of the controversies associated with the use of p-values.

Q

Category: Qualitative data analysis. These pages discuss some of the conceptual and logistical issues associated with the analysis of interviews, focus group data, and other sources of non-quantitative data.

Category: Quality control. These pages discuss some of the organizational and pragmatic issues associated with developing a quality control program.

R

Category: R software. These pages discuss how to program using R software, an open source package for statistical analysis.

Category: Randomization in research. These pages describe the logistics and the ethical issues associated with the use of randomization to allocate patients into the treatment and control groups.

Category: Research design. These pages describe the variety of designs available to a researcher and contrasts their advantages and disadvantages. Articles are arranged by date with the most recent entries at the top.

S

Category: Sample size justification. These pages provide formulas and advice for justifying the sample size in a research study. Some of these pages describe the pragmatic and ethical concerns about sample size.

Category: Small sample size issues. These pages outline some of the practical issues and ethical concerns with small sample sizes.

Category: SPSS software. These pages describe how to use SPSS, a commercial statistical software program, to manage data and perform data analyses.

Category: Statistical computing. These pages describe the computational aspects of statistics.

Category: Statistical evidence. Statistical Evidence is the title of a book I wrote (full title: Statistical Evidence in Medical Trials. What Do the Data Really Tell Us?). There is a variety of supporting material for the book, excerpts from the book, and web pages that contributed information to the first draft of the book.

Category: Statistical theory. These pages describe some of the more mathematical and/or technical aspects of Statistics.

Category: Subgroups in research. See Category: Multiple comparisons

Category: Survey design. These pages discuss how to design a questionnaire or survey.

Category: Survival analysis. Survival data represents data that indicates with information about the time to a certain event (often death, but it can represent other events as well). A common feature for most survival data is the process of censoring. These pages discuss the various ways you can analysis survival data.

Category: Systematic overviews. These pages discuss issues associated with a systematic overview (systematic review, meta-analysis).

T

Category: Teaching resources. These pages present teaching resources that I have found.

U

Category: Unusual data. These pages describe data analysis that does not fit easily into the more traditional categories of data analysis. If I get a sufficient number of pages on the same general topic, I will create a new category.

V

W

Category: Website details. These pages explain new developments at this website.

Category: Wiki pages. These links discuss contributions I have made to various Wiki sites (Chance News and Wikipedia) as well as general discussion about Wiki pages.

Category: Writing research papers. These pages discuss some of the issues that you need to consider when writing about a scientific or medical topic.

X

Y

Z

Here are the older categories and their relationship to the new system.

Ethics

Evidence

Model

Plan

 

Teaching resources

General, see Category: Administrative details

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