hiltfantastic.blogg.se - Statcalc epiinfo

Enter the data from the above Nonsmokers sample table in the first Strata tab (Strata 1).

A blank table opens in the StatCalc application window.

From the StatCalc application main page, select Tables.

To view and create a Stratified Analysis Summary of 2-by-2 Tables, take the following steps: When the effect varies in the different strata (the odds ratios are different), interaction or effect modification is present. In other words, the effect of alcohol on MI is the same for smokers and nonsmokers. Note that the odds ratio in the two strata are the same (1.0) there is no interaction or effect modification between smoking and alcohol. The crude odds ratio and the Mantel summary odds ratio are quite different (4.0 and 1.0), concluding that smoking was a confounding factor and there appears (with this over simplified analysis) to be no association (odds ratio= 1.0) between alcohol and MI.

The odds ratio for each table is 1.0, and the Mantel summary odds ratio is 1.0. Stratifying the data by smoking status creates two tables, one for smokers, and one for nonsmokers. Smoking is known to be associated with MI and alcohol consumption. The following case-control study indicates an apparent association between alcohol consumption and MI with an odds ratio of 2.26. Relationship Between Alcohol Consumption and Myocardial Infarction (MI): Confounding Due to Smoking Hypothetical Data from Schlesselman, p.

The odds ratio of 1.02 and the confidence limits that include 1.0 fail to provide evidence of any association between sweetener use and bladder cancer (cited by Schlesselman, p.

Results will be generated as the different values in the cells are populated.

Enter the data from the above sample table.

Statistical significance can be assessed by p-values for the Chi square tests that are small. The further the odds ratio or relative risk is from 1.0, the stronger the apparent association. Generally, an association is suggested by an odds ratio or relative risk larger or smaller than 1.0. Given a yes-no or other two-choice question describing disease and another describing exposure to a risk factor, StatCalc produces several kinds of statistics that test for relationships between exposure and disease. Carefully observe the labels and transpose data items if necessary. Not all textbooks and articles use the same conventions. The table in StatCalc has Exposure on the left and Disease across the top. Two-by-two tables are frequently used in epidemiology to explore associations between exposure to risk factors and disease or other outcomes. Confounding must be removed by stratifying on confounding variables. The values for one individual do not predict those for another.

For the results to be valid, the outcomes in each record must be independent of those in other records.The odds ratio would, however, be an indicator of the degree of association between illness and the consumption of a particular food. Thus, in a foodborne outbreak, selecting cases and controls from those who ate at a particular restaurant in a given week, the odds ratio could not be used to approximate relative risk if half of the individuals became ill. Fewer than one case in 20 individuals might be taken as a starting point. In case-control studies, the odds ratio may be used as an approximation of the relative risk if the disease is rare in the general population from which cases and controls are selected. In cohort studies, the relative risk may be calculated from the results.A cross-sectional study starts with neither illness nor exposure determined, and ascertains both during the study. In a cohort study, the exposed and unexposed are selected and the number of ill in each group is subsequently ascertained. A case-control study is one in which the ill and well individuals are selected and the number of exposed and unexposed is subsequently ascertained.The values in the cells must be counts representing the number of records meeting the specifications in the marginal and stratum labels.Both single and stratified 2-by-2 tables can be analyzed to produce odds ratios and risk ratios (relative risks) with confidence limits, several types of chi square tests, Fisher exact tests, Mantel-Haenszel summary odds ratios and chi squares, and associated p values Assumptions These tables are similar to those produced in Classic Analysis. How to: Analysis of Single and Stratified Tables