Normal distributed variable
Continuous non-normal distributed variable
Numerical variable forced to be categorical
Categorical variable
Survival variable
Normal distributed variable after applying Shapiro-test
Non-Normal distributed variable after applying Shapiro-test
Numerical variable with few unique values converted to categorical
Notes
Factors or characters variables are treated as categorical and cannot be converted to any other type.
Survival variables are computed in "Recoded variables" panel. They cannot be converted to any other type.
Shapiro tests cannot be computed when sample size is bigger than 5,000. If this is the case, it will suposed to be normal distributed. You can also perform a plot ("Plot panel") to test normality.
compare
Create data summaries for quality control, extensive reports for exploring data, as well as publication-ready univariate or bivariate tables in several formats:
plain text (csv), HTML, PDF, Word or Excel
Perform figures to quickly visualise the distribution of your data (boxplots, barplots, normality-plots, etc.).
Display statistics (mean, median, frequencies, incidences, etc.)
Perform the appropriate tests (t-test, Analysis of variance, Kruskal-Wallis, Fisher, log-rank, ...) depending on the nature of the described variable (normal, non-normal or qualitative).
Summarize genetic data (Single Nucleotids Polymorphisms) data displaying Allele Frequencies and performing Hardy-Weinberg Equilibrium tests among other typical statistics and tests for these kind of data.
compare
This WUI is designed to allow clinicians and scientists to take advantage of the functionality of compareGroups to analyse their epidemiological data, but without the need to install or learn how to use R.
This system has all of the functionality of the current command line version of compareGroups, but has the advantage of allowing you to load and analyse your data on any device with an internet connection.
This WUI has been build entirely using Shiny tools.
Data Security when using the compare
compareGroups is developed by experienced researchers who are actively involved in epidemiological research on human subjects. We understand very well how important it is to guarantee data confidentiality and security, and we have designed the compareGroups WUI so that your data will remain as secure as at your own institute.
Will my data be safe if I load them into the compareGroups WUI?
The compareGroups WUI is hosted on a secure cloud server platform, which guarantees the physical and electronic security of the WUI, and therefore of any data that are loaded into it. Data loaded into the WUI are transmitted over a secure connection via HTTPS.
What happens to my data when I load them into the compareGroups WUI?
If you're familiar with R, you'll know that it loads all data and performs all calculations within the RAM allocated for that R session. This means that it never writes data to the disk, and when the R session ends, all data it has been working on are eliminated.
Accessing the compareGroups WUI page starts a dedicated session of R to read and manipulate your data, and compute your results. However, this R session never saves data to the hard disk of the server it's running on, and only sends results to the WUI, either in the form of displayed tables or plots, or as files to be downloaded by the the user via the SAVE panel.
When you close your browser window, the R session is terminated, and all data are lost. To can verify this for yourself by simply re-loading the WUI page, after which you will see that no data are loaded. compareGroups developers only have access to the underlying R code that generates that WUI and performes the calculations, and can never gain access to data that have been loaded into a remote session.
If you have any further concerns or questions about the security of your data when using the compareGroups WUI, please get in touch with us via the contact form.
REGICOR: These data come from 3 different cross-sectional surveys of individuals representative of the population from a north-west Spanish province (Girona), REGICOR study. It contains 2294 observations on 21 variables such as age, sex, cholesterol profile hypertension, etc.)
PREDIMED: The PREDIMED trial (Prevención con Dieta Mediterránea) is a randomized, parallel and multicentric cohort with more than 7,000 participants who were randomly assigned to three diet groups (olive oil + mediterranean diet, nuts + mediterranean diet, and low-fat diet -control group-) and followed-up during more than 7 years.data frame with 6324 observations on the following 15 variables. It contains 6324 observations on 15 variables such as age, sex, diabetes status as well as cardiovascular events during the follow-up time. For more information about the study these data come from, visit http://predimed.onmedic.net
SNPs: A data.frame containing 35 selected SNPs and other clinical covariates for 110 cases and 47 controls in a case-control study.
It may be necessary to refresh the web page when loading a new data set.
Browse and select your file containing the data.
Once the file is uploaded a dropdown list appears, where you must choose the format (SPSS, TXT, Excel or R).
Set up read options depending on the file format:
If you have selected TEXT format, a panel will appear where you have to set the right TEXT Options so that your data can be read correctly, such as variable separators, decimal character, etc.
If you have selected Excel, a dropdown list of sheets name will apear to chose one of them.
If you have selected R-format, a dropdown list of data.frame objects will apear to chose one of them. Matrices data sets will not appear.
Step 4. Press "Read" button to read the data and the data.frame will appear on the right side panel.
Change the Encoding options to get sure that non-standard characters such as "ñ", "ç", etc. are read correctly.
It may be necessary to refresh the web page when loading a new data set.