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Note

title	Prerequisites

It is recommended that you familiarise yourself with R first by sitting our Introduction to R tutorial.

It also requires that you have the DataSHIELD training environment installed on your machine, see our Installation Instructions for Linux, Windows, or Mac.

Tip

title	Help

DataSHIELD support is freely available in the DataSHIELD forum by the DataSHIELD community. Please use this as the first port of call for any problems you may be having, it is monitored closely for new threads.

DataSHIELD bespoke user support and also user training classes are offered on a fee-paying basis. Please enquire at datashield@newcastle.ac.uk for current prices.

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The other parts in this DataSHIELD tutorial series are:

Quick reminder for logging in:

Follow instructions to Start the Opal VMs.

Recall from the installation instructions, the Opal web interface is a simple check to tell if the VMs have started. Load the following urls, waiting at least 1 minute after starting the training VMs.

http://192.168.56.100:8080

http://192.168.56.101:8080

Expand

Start R/RStudio

Load Packages

Code Block

	xml
	xml

#load libraries
library(DSI)
library(DSOpal)
library(dsBaseClient)

Build your login dataframe

Code Block

language	xml
title	Build your login dataframe

builder <- DSI::newDSLoginBuilder()
builder <- DSI::newDSLoginBuilder()
builder$append(server = "study1server1",  url = "httphttps://192.168.56.100:8080/",
              opal-demo.obiba.org/",
user = "administratordsuser", password = "datashield_test&P@ssw0rd",                table driver = "CNSIM.CNSIM1OpalDriver", driver = "OpalDriver"options='list(ssl_verifyhost=0, ssl_verifypeer=0)')
builder$append(server = "study2server2", url = "httphttps://192opal-demo.168.56.101:8080obiba.org/",
              
user = "administratordsuser", password = "datashield_test&P@ssw0rd", driver =              table = "CNSIM.CNSIM2", driver = "OpalDriver""OpalDriver", options='list(ssl_verifyhost=0, ssl_verifypeer=0)')

logindata <- builder$build()

logindata <- builder$build()

connections <- DSI::datashield.login(logins = logindata, assign = TRUE)
DSI::datashield.assign.table(conns = connections, symbol = "DST", "D"table = c("CNSIM.CNSIM1","CNSIM.CNSIM2"))

Command to logout:

Code Block

language	bash

DSI::datashield.logout(connections)

...

Code Block

language	xml

ds.log(x='D$LABDST$LAB_HDL', datasources = connections)

...

Code Block

theme	RDark

  Aggregated (exists("DDST")) [=============================================================] 100% / 0s
  Aggregated (classDS("D$LABDST$LAB_HDL")) [====================================================] 100% / 1s
  Assigned expr. (log.newobj <- log(D$LABDST$LAB_HDL,2.71828182845905)) [=======================] 100% / 0s
  Aggregated (exists("log.newobj")) [====================================================] 100% / 0s

...

Code Block

language	xml

ds.log(x='D$LABDST$LAB_HDL', newobj='LAB_HDL_log', datasources = connections)

...

Code Block

language	xml

ds.assign(toAssign='D$LABDST$LAB_HDL-1.562', newobj='LAB_HDL.c', datasources = connections)

...

Code Block

language	xml

ds.table(rvar="D$GENDERDST$GENDER")

Code Block

theme	RDark

  Aggregated (asFactorDS1("D$GENDERDST$GENDER")) [=================================================] 100% / 0s
  Aggregated (tableDS(rvar.transmit = "D$GENDERDST$GENDER", cvar.transmit = NULL, stvar.transmit = NULL, ) ...

 Data in all studies were valid 

Study 1 :  No errors reported from this study
Study 2 :  No errors reported from this study

$output.list
$output.list$TABLE_rvar.by.study_row.props
        study
D$GENDERDST$GENDER         1         2
       0 0.4079193 0.5920807
       1 0.4160839 0.5839161

$output.list$TABLE_rvar.by.study_col.props
        study
D$GENDERDST$GENDER         1         2
       0 0.5048544 0.5132772
       1 0.4951456 0.4867228

$output.list$TABLE_rvar.by.study_counts
        study
D$GENDERDST$GENDER    1    2
       0 1092 1585
       1 1071 1503

$output.list$TABLES.COMBINED_all.sources_proportions
D$GENDERDST$GENDER
   0    1 
0.51 0.49 

$output.list$TABLES.COMBINED_all.sources_counts
D$GENDERDST$GENDER
   0    1 
2677 2574 


$validity.message
[1] "Data in all studies were valid"

...

Code Block

language	xml

ds.table(rvar='D$DISDST$DIS_DIAB', cvar='D$GENDERDST$GENDER', datasources = connections)

...

Code Block

theme	RDark

  Aggregated (asFactorDS1("D$DISDST$DIS_DIAB")) [===============================================] 100% / 0s
  Aggregated (asFactorDS1("D$GENDERDST$GENDER")) [=================================================] 100% / 0s
  Aggregated (tableDS(rvar.transmit = "D$DISDST$DIS_DIAB", cvar.transmit = "D$GENDERDST$GENDER", ) [======] 100% / 0s

 Data in all studies were valid 

Study 1 :  No errors reported from this study
Study 2 :  No errors reported from this study

$output.list
$output.list$TABLE.STUDY.1_row.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB     0     1
         0 0.502 0.498
         1 0.700 0.300

$output.list$TABLE.STUDY.1_col.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB      0      1
         0 0.9810 0.9920
         1 0.0192 0.0084

$output.list$TABLE.STUDY.2_row.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB     0     1
         0 0.511 0.489
         1 0.660 0.340

$output.list$TABLE.STUDY.2_col.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB      0      1
         0 0.9800 0.9890
         1 0.0196 0.0106

$output.list$TABLES.COMBINED_all.sources_row.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB     0     1
         0 0.507 0.493
         1 0.675 0.325

$output.list$TABLES.COMBINED_all.sources_col.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB      0       1
         0 0.9810 0.99000
         1 0.0194 0.00971

$output.list$TABLE_STUDY.1_counts
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB    0    1
         0 1071 1062
         1   21    9

$output.list$TABLE_STUDY.2_counts
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB    0    1
         0 1554 1487
         1   31   16

$output.list$TABLES.COMBINED_all.sources_counts
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB    0    1
         0 2625 2549
         1   52   25


$validity.message
[1] "Data in all studies were valid"

...

The function can additionally compute a chi-squared test for homogeneity on (nc-1)*(nr-1) degrees of freedom (where nc is the number of columns and nr is the number of rows):

Code Block

language	xml

ds.table(rvar='DST$DIS_DIAB', cvar='DST$GENDER', datasources = connections, report.chisq.tests = TRUE)

Below code omits the first section of output which is an exact duplicate of above, only chisquare reports shown:

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The other parts in this DataSHIELD tutorial series are:

Tip

Also remember you can:

get a function list for any DataSHIELD package and
view the manual help page individual functions
in the DataSHIELD test environment it is possible to print analyses to file (.csv, .txt, .pdf, .png)
take a look at our FAQ page for solutions to common problems such as Changing variable class to use in a specific DataSHIELD function.
Get support from our DataSHIELD forum.

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Versions Compared

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Key

Quick reminder for logging in:

Start R/RStudio

Load Packages

Build your login dataframe