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) ...
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...
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...
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...
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...
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 In an attempt to make it simpler, we will call Y the response variable that we want to explain by X factors. (Use...
When the response variable is binary and not censored, the appropriate statistical model is logistic regression; When there is only one explanatory variable which is categorical, the logistic regression yields a result similar to a Chi2 test; In an attempt to simplify this, we will name Y the variable that...
When the outcome variable is numerical and continuous, the appropriate statistical model is the linear regression When there is only one explanatory variable which is categorical, 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...
We can consider the following three types of analyses: single variable descriptive statistics, univariable analyses (often named univariable) and multivariable (often unproperly named multivariate) analyses Single variable descriptive statistics are used to describe the data, and are useful for detecting problems Univariable and multivariable analyses allow statistical comparisons (obtaining a p-value), and...
In statistical modeling, it is often necessary to group the values 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 relationship...