Several steps are necessary to perform a multivariable (multivariate) analysis: Formalizing the research hypothesis Select the outcome variable Y Select the explanatory variables X Identify covariates Check that the conditions are met Check the robustness of the model Formalizing the research hypothesis All research requires hypotheses to be made. For example, it...
It is necessary to have a basic knowledge of the use of Excel to be able to create new columns. Be careful, it is useless and not recommended to transform numerical variables (e. g. age) to create categories (<20; 20-55; >55 for instance) because this leads to a loss of information....
Essential concepts Excel is organized as a table, containing rows, columns and their intersection: the cells. The rows are numbered, the columns are identified by a letter (for example the 3rd column is cell C). A cell is referred to by its column letter followed by its row number (E1 is...
You have a study to carry out? Great! We have prepared a list of 10 rules to follow in order to make your data analyzable by a statistical software. Which data entry software to choose? First of all, you will need to define on which file format you will input the data....
In statistical modeling, it is often necessary to group the numerical variables to create classes in order to meet the conditions of the model. If we have no a priori idea about the appropriate grouping, it is preferable to base ourselves on the splines representing the link between the...
It is sometimes surprising not to be able to carry out a multivariable analysis because the number of subjects is too small while the file contains several hundred observations (patients, subjects). Linear regressions For linear regressions, i. e. multivariable analyses for which the outcome variable is numerical, it is necessary to have...