Analysis of epidemiological data using r and epicalc. You might see tables that are flipped the layout of tables here is the following. A population based case control study was conducted in northern norway and central. History, case control methods up to modern times the sophisticated use and understanding of case control studies is the most important methodologic development of. This means that for every case there is a control who has the same or closely similar values of the matching variables. How to conduct conditional cox regression for matched case control study. Matching is often used in casecontrol control studies to ensure that the cases and controls are similar in certain characteristics, and it is a useful technique to increase the efficiency of the study. This module should be installed from within stata by typing ssc install cmatch. This is clearly not the case in any 1m matched study. Nested casecontrol and case cohort studies an introduction and some new developments precourse. Introduction matched case control data use of weights fixedeffects logit. A discussion of statistical methods for matched data analysis. Frequency matching is when cases and controls are matched by group, rather than by individual.
Statistical considerations in the analysis of matched case. For example, we might match the sex of the control to the sex of the case. Compare matched groups on matching variables for non. The code below for creating the data set can be copied to the stata dofile editor and be executed through the dofile editor. Case control studies are a common and efficient means. Teaching\stata\stata version 14\stata version 14 spring 2016\stata for categorical data analysis. Parsons, ovation research group, seattle, washington abstract a case control matched analysis is often used in observational studies to reduce selection bias and approximate a randomize d trial. However, matching in a case control study does not control for. Analysis of case control studies the odds ratio or is used in case control studies to estimate the strength of the association between exposure and outcome. Frontiers unconditional or conditional logistic regression. Analytic methods for matched case control studies include conditional logistic regression, conditioned upon the matching. In casecontrol studies, matching forces the ratio of cases to controls to be constant across all strata of the matched factors, which implies that the association between the confounders and the outcome is broken. Statistical inference in matched casecontrol studies of. Matching on demographic variables is commonly used in case control studies to adjust for confounding at the design stage.
Installation guide updates faqs documentation register stata technical services. Title, the appropriate command for matched casecontrol data. In case control studies, matching forces the ratio of cases to controls to be constant across all strata of the matched factors, which implies that the association between the confounders and the outcome is broken. This thesis focuses on some methodological aspects in the analysis of the results from this kind of study. Chapter 17 introduces polytomous logistic regression using a case control study in which one type of case series is compared with two types of control groups. Create new dataset for matched demanders and suppliers 4. Stata module to match cases and controls using specified variables, statistical software components s457372, boston college department of economics, revised 27 jan 2015. Teaching\ stata \ stata version 14\ stata version 14 spring 2016\ stata for categorical data analysis. Currently, sas does not offer the diagnostics discussed in this section. Syntax data analysis and statistical software stata. The other basic type is a matched case control study. Author support program editor support program teaching with stata examples and datasets web resources training stata conferences. Casecontrol study designs are used to estimate the relative risk for a disease from a specific risk factor. Strategy for data analysis for casecontrol studies describe study profile.
Methods of analysis may differ with theses different sizes. Analysis of casecontrol studies the odds ratio or is used in case control studies to estimate the strength of the association between exposure and outcome. Using a comprehensive set of search criteria we identified 37 matched casecontrol studies for detailed analysis. How to find the controls from a subset of cases in an already case. A discussion of statistical methods for matched data. Logistic regression for matched casecontrol studies idre stats. Using a comprehensive set of search criteria we identified 37 matched case control studies for detailed analysis. In a standard case control study, the investigator compares a group of controls with a group of cases. Analyze outcome variables for any significant group. The idea in matching is to match upon a potential confounding variable in order to remove the confounding effect. An introduction to categorical analysis by alan agresti. Stratified models for the odds ratio matched case control. There is a presumption that matched data need to be analyzed by matched methods. Matched case control studies are a classical epidemiology study design.
Matching on factors such as age and sex is commonly used in casecontrol studies. The appropriate command for matched casecontrol data. Conditional logistic regression has become a standard for matched case control data to tackle the sparse data problem. Matched case control studies dependency within matched paircluster. Matching on demographic variables is commonly used in casecontrol studies to adjust for confounding at the design stage. The data files used for the examples in this text can be downloaded in a zip file. Multivariate analysis and hypothesis testing clogit. In order to perform the analysis, stata will require you to have casecontrol status coded as. Feb 19, 20 this feature is not available right now. In both types of study cases and controls are sometimes matches. The matched pair case control study calculates the statistical relationship between exposures and the likelihood of becoming ill in a given patient population.
Logistic regression for matched casecontrol studies stata textbook examples. Jan 19, 2016 case control study o it is an observational study in which subjects are sampled based upon presence or absence of disease and then their prior exposure status is determined. Casecontrol studies can usually be conducted relatively faster and are inexpensive particularly when compared with cohort studies. Openepi sample size for unmatched casecontrol studies.
The significance of the association between a categorical risk factor and case status can be tested using mcnemars test, or by attaching a confidence interval to the odds ratio. When each case is matched to one control, we say that the study is 1. Pdf elementary epidemiological data analysis using stata. You wont remember all the details, but you will at least know what basic commands are available. Models for matched pairs stata textbook examples section 9. How to conduct conditional cox regression for matched case. This module should be installed from within stata by typing ssc install ccmatch. Analysis of frequency matched case control studies. Using propensity scores to reduce casecontrol selection bias.
The 2,988 breast cancer cases were linked to the drivers license file to determine whether cases matched a record from the masterfile of drivers. History, casecontrol methods up to modern times the sophisticated use and understanding of casecontrol studies is the most important methodologic development of unmatched cc study modern epidemiology rothman textbook 1986, p. Logistic regression for matched casecontrol studies. Regression models for casecontrol and matched studies 1 agenda quoted in breslow 1996.
A discussion of statistical methods for matched data analysisfor matched data analysis mingfu liu. Phd, dcs methodology journal club presentation oct 5, 2010oct 5, 2010 1. Is there any reading material which can give me an idea of doing analysis in a matched case control study. The primary focus here is on the analysis of matched case control studies using conditional logisticregression, but one can also fit stratified models using. Comprehensive summaries of uppsala dissertations from the faculty of social sciences 100. I have a dataset that has cases and controls matched on age, gender and number of years. Both exposure and outcome disease have occurred before the start of the study. Matched cohort methods for injury research epidemiologic. Similar results were found in another re analysis of breast cancer risk. Can anyone advise me on the matched case control study. Note that it is not possible to estimate the incidence of disease from a case control study unless the study is population based and all cases in a defined population are obtained.
However, matching in a casecontrol study does not control for confounding by the matching factors. Applied logistic regression, second edition, by hosmer and lemeshow. If the matching is exact, accounting for the matching in the analysis will. If you do have a nested casecontrol study, i would be more. Improving case control study validity by addressing drivers license sampling frame limitations. Stratified models for the odds ratio matched case control studies this section contains examples that illustrate the use of gmbopecan to fit stratified models for the odds ratio. For the love of physics walter lewin may 16, 2011 duration. Statistical considerations in the analysis of matched case control studies. This study is used to investigate a cause of an illness by selecting a nonill person as the control and matching the control to a case. In a matched study, we enroll controls based upon some characteristics of the case.
This can be done using nested likelihood ratio tests as we did when. Crosstabulation in cohort and casecontrol studies the. Spssx discussion matched case control data analysis help. Stata does not limit itself to incidence rate cohort studies. Analysis of matched cohort data is not discussed in many textbooks or articles and is not mentioned in the stata manuals. Matching is intended to eliminate confounding, however, the main potential benefit of matching in case control studies is a gain in efficiency. Sample size for matched casecontrol studies statsdirect. This happens in epidemiological case control studies, where a possible risk factor is compared between cases and controls to investigate the nature of the disease.
An introduction to matching and its application using sas. Conditional logistic regression has become a standard for matched casecontrol data to tackle the sparse data problem. Feb 25, 2016 however, there is a small increase in precision in the matched case control study compared with the unmatched case control studies 95% confidence intervals of 1. The estimate is the odds ratio, which is a good estimate of the relative risk especially when the disease is rare.
Individually matched case control study designs are frequently found in public health and medical literature, and conditional logistic regression is the tool most commonly used to analyze these studies. Ill copy from the stata survival analysis and epidemiological tables reference manual. The case control study is one of the most frequently used study designs in analytical epidemiology. This example adapted from intuitive biostatistics helps you use the mcnemars test calculator that is part of graphpad quickcalcs. Randomness in the matching is obtained using stata s runiform function. Aug 01, 2003 when matching is done in a case control study, those with the outcome are matched to those without the outcome on certain confounder measures.
Those two will familiarize you with the basic commands that are commonly used in stata data management and analysis. Stratified analysis of casecontrol data in stata youtube. An introduction to categorical analysis by alan agresti chapter 9. In this paper i explore and illustrate these problems using a hypothetical pair matched case control study. Epi info provides interactive analysis of surveillance system data. There are two common misconceptions about casecontrol studies. Stata has an addon program called clfit that will generate these diagnostic variables after clogit. Power analysis for matched casecontrol studies stata. If you are using more than one control per case then this function also provides the reduction in sample size relative to a paired study that you can obtain using your number of controls per case dupont, 1988. Capitalizing on the emerging consensus on the validity of the use of ulr with adjustment for matching variables for individually matched casecontrol studies, 18, 20, 22 we propose a strategy for analysis of casecontrol studies that use the concurrent design, which involves matching for time, a continuous variable. When you have used a casecontrol design for the diarrhea study, the actual crosstabulation is quite similar, only presence of diarrhea yesno, is now changed into cases and controls. Logistic regression for matched case control studies stata textbook examples the data files used for the examples in this text can be downloaded in a zip file from the wiley publications website.
In this matched study design, unlike in case control studies, there is. Combining matched and unmatched control groups in case. In an analysis of a matched study design, only discordant pairs are used. Analysis of matched case control studies neil pearce1,2 there are two common misconceptions about case control studies. The sparse data problem, however, may not be a concern for loose.
However, matching in a case control study does not control for confounding by the matching factors. A propensity score is the predicted probability of an outcome. The tests will performed in two statistical analysis packages, stata and. Finally, conditional logistic regression is applied. Applied logistic regression, second edition, by hosmer and lemeshow chapter 7. Analysis of case control studies foodborne disease. Sample size for unmatched case control studies, version 3. Again assume that sampling to case control study does only depend on. Matched casecontrol studies are a classical epidemiology study design. The subjects in the different case and control groups are matched on potentially. When the resulting dataset is analyzed as a matched case control study, odds ratios will estimate corresponding rateratio parameters in the proportional hazards model for the cohort study. A discordant pair occurs when the exposure status of case is different than the exposure status of the control. In fact, the more standard analysis may not only be valid but may be much easier in practice, and yield bet ter statistical precision.