## 11 MarManagement of Covariates

This page aims to describe the methodological choices regarding both the selection of variables and their modeling. This page is technical. The R code corresponding to the descriptions below is available here. Variable selection Definitions We differentiate between two types of covariates (variables included into a model but not being the main explanatory/predictor...

## 11 MarDescriptive, explanatory and predictive analyses

One typology of statistical analyses is based on their purpose: Descriptive analyses, to describe the variables, either individually (descriptive statistics), or by cross-tabulating them with another variable (by performing univariables analyses) Explanatory analyses, to determine the influence of one or more variables on another (for example using an Odds Ratio) ...

## 11 MarAutomatic test selection

The purpose of this page is to describe the methodological choices regarding the tests performed on pvalue.io. This page is technical, and is intended for users wondering why one test is performed rather than another. The corresponding R code is available here. Univariable test The test performed depends on the type of...

## 23 SepIs pvalue.io reliable?

First of all, it is important to be aware that no statistical software guarantees the results it provides, even the most widely used software (including Excel). pvalue.io is still new. It is a graphical interface to R, which is a reference statistical analysis software, as well as SAS, Stata and SPSS. To...

## 27 NovHow to perform an explanatory analysis

Several steps are necessary to perform an explanatory analysis: Elicit the research hypothesis Select the response (explained) variable Y Select the main explanatory variable X Identify the covariates Check that the conditions are met Check the robustness of the model Elicit the research hypothesis All research requires hypotheses. For example, it may...

## 18 OctShould medical students learn statistics?

Statistics are often considered complex and far from daily clinical practice. Legitimately, as a doctor or student, one may wonder whether it is useful to learn biostatistics and to perform statistical analyses by oneself. Learn statistics? It is quite possible to learn the basics of statistics without having a solid knowledge of...

## 22 JulSurvival analysis

When the response variable is binary and it is possible to switch permanently from one state to another, we can carry out survival analyses This type of analysis can take into account the lost to follow-up The most commonly used statistical model for survival analysis in medical studies is...

## 17 JulCreate new “calculated” columns using Excel

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....

## 16 JulThe basics of Excel

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...

## 16 JulHow to prepare a file for statistical analysis of a clinical study?

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....