View source: R/ds.meanByClass.R
ds.meanByClass | R Documentation |
This function calculates the mean and the standard deviation (SD) of a continuous variable for each class of up to 3 categorical variables.
ds.meanByClass(
x = NULL,
outvar = NULL,
covar = NULL,
type = "combine",
datasources = NULL
)
x |
a character string specifying the name of the dataset or a text formula. |
outvar |
a character vector specifying the names of the continuous variables. |
covar |
a character vector specifying the names of up to 3 categorical variables |
type |
a character string that represents the type of analysis to carry out.
|
datasources |
a list of |
The function splits the input dataset into subsets (one for each category) and calculates
the mean and SD of the specified numeric variables. It is important to note that the process of
generating the final table(s) can be time consuming particularly if the subsetting is done across
more than one categorical variable and the run-time lengthens if the parameter type
is set to
'split'
as a table is then produced for each study. It is therefore advisable to run the function
only for the studies of the user interested in but including only those studies in the
parameter datasources
.
Depending on the variable type
can be carried out two analysis:
(1) 'combine'
: a pooled table of results is generated.
(2) 'split'
: a table of results is generated for each study.
ds.meanByClass
returns to the client-side a table or a list of tables that
hold the length of the numeric variable(s) and their mean
and standard deviation in each subgroup (subset).
DataSHIELD Development Team
ds.subsetByClass
to subset by the classes of factor vector(s).
ds.subset
to subset by complete cases (i.e. removing missing values), threshold, columns and rows.
## Not run:
## Version 6, for version 5 see the Wiki
# connecting to the Opal servers
require('DSI')
require('DSOpal')
require('dsBaseClient')
builder <- DSI::newDSLoginBuilder()
builder$append(server = "study1",
url = "http://192.168.56.100:8080/",
user = "administrator", password = "datashield_test&",
table = "CNSIM.CNSIM1", driver = "OpalDriver")
builder$append(server = "study2",
url = "http://192.168.56.100:8080/",
user = "administrator", password = "datashield_test&",
table = "CNSIM.CNSIM2", driver = "OpalDriver")
builder$append(server = "study3",
url = "http://192.168.56.100:8080/",
user = "administrator", password = "datashield_test&",
table = "CNSIM.CNSIM3", driver = "OpalDriver")
logindata <- builder$build()
connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D")
#Calculate mean by class
ds.meanByClass(x = "D",
outvar = c('LAB_HDL','LAB_TSC'),
covar = c('PM_BMI_CATEGORICAL'),
type = "combine",
datasources = connections)
ds.meanByClass(x = "D$LAB_HDL~D$PM_BMI_CATEGORICAL",
type = "combine",
datasources = connections[1])#Only the frist server is used ("study1")
# clear the Datashield R sessions and logout
datashield.logout(connections)
## End(Not run)
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