## 27 NovHow to perform a multivariable analysis

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 the adjustment variables Check that the conditions are met Check the robustness of the model Formalizing the research hypothesis All research requires hypotheses to be made. For...

## 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 outcome 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?

That's it, 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 biostatistics software. Which data entry software to choose? AFirst of all, it is necessary to define on which file format you will input...

## 11 JulMissing data handling

When a parameter has not been measured for all patients in the study, we are talking about missing data There are few studies without missing data If missing data are present, they should be described and a strategy chosen to address them Missing data is a common problem in the...

## 10 JulConditions of Regression Models

Tests and statistical models all have conditions to be used.In this article, we describe the conditions of regression models, as well as how they are checked by pvalue.io Dans un effort de simplification, nous appellerons Y la variable que l'on souhaite expliquer par des facteurs X. (Faites appel à vos lointains...

## 08 JulLogistic regression

When the outcome variable is binary and not censored, the appropriate statistical model is logistic regression; When there is only one explanatory variable which is qualitative, the logistic regression yields a result similar to a Chi2 test; In an attempt to simplify this, we will name Y the variable that...

## 04 JulLinear regressions

When the outcome variable is quantitative and continuous, the appropriate statistical model is the linear regression When there is only one explanatory variable which is qualitative, linear regression yields a result close to a Welch or Student T test In an attempt to simplify this, we will name Y the variable that...