EZR.dialogs: EZR dialogs
In RcmdrPlugin.EZR: R Commander Plug-in for the EZR (Easy R) Package
EZR dialogs R Documentation
EZR dialogs
Description
EZR dialogs enable point-and-click easy access to a variety of statistical functions.
Details
EZR dialogs enable point-and-click easy access to a variety of statistical functions.
To select more than one variable in the list box, click on variables pressing Ctrl key, and to deselct one of the selected variables, click on the variable to deselect pressing Ctrl key.
To perform analyses in a subset of the samples, type an R expression into the box labelled "Condition to limit samples for analysis". For example, to perform analysis in male patients aged at least 60 years old, type Age >= 60 & Sex == "Male" into the box, assuming that Age and Sex variables indicate age and sex of the patients, respectively.
Cautions in multivariate analyses using EZR
When a categorical variable with more than two categories is to be analyzed in Fine and Gray regression modeling, dummy variables should be created before an analysis, although such dummy variables are automatically created in multiple regression, logistic regression and Cox proportional hazards regression in R. For example, if a user wants to evaluate the effect of three types (A, B, and C) of treatments, information for which is included in the categorical variable Tx as "A", "B" and "C", they would select "Active data set" > "Variables" > "Create dummy variables" from the EZR menu to make three categorical variables named Tx.Dummy.A, Tx.Dummy.B, and Tx.Dummy.C.
Tx.Dummy.A has a value of 1 for patients who received treatment A and 0 for others. Users should choose one of the three categories as a reference and input dummy variables for the other two categories into the regression model.
The stepwise selection function of explanatory variables based on Akaike information criterion and Bayesian information criterion only accepts dummy variables automatically created by R, whereas stepwise selection based on P-value also accepts dummy variables created by a user using EZR. If the option for a "Wald test for overall P-value for factors with >2 levels" is selected in the dialog of the regression analyses, the overall P-value for the categorical variable will be calculated.
Survival curves adjusted for other factors by the mean of covariates method, in which average values of covariates are entered into the Cox proportional hazards model, can be drawn by selecting "Graphs" > "Adjusted survival curve".
References
Read follwing article for details. It can be freely downloaded from the journal website as shown below.
Yoshinobu Kanda (2012).
Investigation of the freely available easy-to-use software EZR for medical statistics.
Bone Marrow Transplantation (Open article, URL: https://www.nature.com/articles/bmt2012244.pdf).
RcmdrPlugin.EZR documentation built on Oct. 24, 2023, 5:06 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| EZR dialogs | R Documentation |
EZR dialogs
Description
EZR dialogs enable point-and-click easy access to a variety of statistical functions.
Details
EZR dialogs enable point-and-click easy access to a variety of statistical functions.
To select more than one variable in the list box, click on variables pressing Ctrl key, and to deselct one of the selected variables, click on the variable to deselect pressing Ctrl key.
To perform analyses in a subset of the samples, type an R expression into the box labelled "Condition to limit samples for analysis". For example, to perform analysis in male patients aged at least 60 years old, type Age >= 60 & Sex == "Male" into the box, assuming that Age and Sex variables indicate age and sex of the patients, respectively.
Cautions in multivariate analyses using EZR
When a categorical variable with more than two categories is to be analyzed in Fine and Gray regression modeling, dummy variables should be created before an analysis, although such dummy variables are automatically created in multiple regression, logistic regression and Cox proportional hazards regression in R. For example, if a user wants to evaluate the effect of three types (A, B, and C) of treatments, information for which is included in the categorical variable Tx as "A", "B" and "C", they would select "Active data set" > "Variables" > "Create dummy variables" from the EZR menu to make three categorical variables named Tx.Dummy.A, Tx.Dummy.B, and Tx.Dummy.C.
Tx.Dummy.A has a value of 1 for patients who received treatment A and 0 for others. Users should choose one of the three categories as a reference and input dummy variables for the other two categories into the regression model.
The stepwise selection function of explanatory variables based on Akaike information criterion and Bayesian information criterion only accepts dummy variables automatically created by R, whereas stepwise selection based on P-value also accepts dummy variables created by a user using EZR. If the option for a "Wald test for overall P-value for factors with >2 levels" is selected in the dialog of the regression analyses, the overall P-value for the categorical variable will be calculated.
Survival curves adjusted for other factors by the mean of covariates method, in which average values of covariates are entered into the Cox proportional hazards model, can be drawn by selecting "Graphs" > "Adjusted survival curve".
References
Read follwing article for details. It can be freely downloaded from the journal website as shown below.
Yoshinobu Kanda (2012).
Investigation of the freely available easy-to-use software EZR for medical statistics.
Bone Marrow Transplantation (Open article, URL: https://www.nature.com/articles/bmt2012244.pdf).
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.