ds.table2D {dsBaseClient}

R Documentation

Generates 2-dimensional contingency tables

Description

The function ds.table2D is a client-side wrapper function. It calls the server-side function 'table2DDS' that generates a 2-dimensional contingency table for each data source.

Usage

ds.table2D(
  x = NULL,
  y = NULL,
  type = "both",
  warningMessage = TRUE,
  datasources = NULL
)

Arguments

x	a character, the name of a numerical vector with discrete values - usually a factor.
y	a character, the name of a numerical vector with discrete values - usually a factor.
type	a character which represent the type of table to ouput: pooled table or one table for each data source or both. If type is set to 'combine', a pooled 2-dimensional table is returned; If type is set to 'split' a 2-dimensional table is returned for each data source. If type is set to 'both' (default) a pooled 2-dimensional table plus a 2-dimensional table for each data source are returned.
warningMessage	a boolean, if set to TRUE (deafult) a warning is displayed if any returned table is invalid. Warning messages are suppressed if this parameter is set to FALSE. However the analyst can still view 'validity' information which are stored in the output object 'validity' - see the list of output objects.
datasources	a list of DSConnection-class objects obtained after login. If the <datasources> the default set of connections will be used: see datashield.connections_default.

Details

The table returned by the server side function might be valid (non disclosive - no table cell have counts between 1 and the minimal number agreed by the data owner and set in the data repository as the "nfilter.tab") or invalid (potentially disclosive - one or more table cells have a count between 1 and the minimal number agreed by the data owner). If a 2-dimensional table is invalid all the cells are set to NA except the total counts. In this way, it is possible to combine total counts across all the data sources but it is not possible to identify the cell(s) that had the small counts which render the table invalid.

Value

A list object containing the following items:

colPercent	table(s) that hold column percentages for each level/category. Inner cells are reported as missing if one or more cells are 'invalid'.
rowPercent	table(s) that hold row percentages for each level/category. Inner cells are reported as missing if one or more cells are 'invalid'.
chi2Test	Chi-squared test for homogeneity.
counts	table(s) that hold counts for each level/category. If some cell counts are invalid (see 'Details' section) only the total (outer) cell counts are displayed in the returned individual study tables or in the pooled table.
validity	a text that informs the analyst about the validity of the output tables. If any tables are invalid the studies they are originated from are also mentioned in the text message.

Author(s)

Amadou Gaye, Paul Burton, Demetris Avraam, for DataSHIELD Development Team

See Also

ds.table1D for the tabulating one vector.

Examples

## Not run: 

  # load the file that contains the login details
  data(logindata)

  # login and assign all the variables to R
  conns <- datashield.login(logins=logindata,assign=TRUE)

  # Example 1: generate a two dimensional table, outputting combined contingency
  # tables - default behaviour
  output <- ds.table2D(x='D$DIS_DIAB', y='D$GENDER')
  # display the 5 results items, one at a time to avoid having too much information
  # displayed at the same time
  output$counts
  output$rowPercent
  output$colPercent
  output$chi2Test
  output$validity

  # Example 2: generate a two dimensional table, outputting study specific contingency tables
  ds.table2D(x='D$DIS_DIAB', y='D$GENDER', type='split')
  # display the 5 results items, one at a time to avoid having too much information displayed
  at the same time
  output$counts
  output$rowPercent
  output$colPercent
  output$chi2Test
  output$validity

  # Example 3: generate a two dimensional table, outputting combined contingency tables
  # *** this example shows what happens when one or studies return an invalid table ***
  output <- ds.table2D(x='D$DIS_CVA', y='D$GENDER', type='combine')
  output$counts
  output$rowPercent
  output$colPercent
  output$chi2Test
  output$validity

  # Example 4: same example as above but output is given for each study,
  # separately (i.e. type='split')
  # *** this example shows what happens when one or studies return an invalid table ***
  output <- ds.table2D(x='D$DIS_CVA', y='D$GENDER', type='split')
  output$counts
  output$rowPercent
  output$colPercent
  output$chi2Test
  output$validity

  # clear the Datashield R sessions and logout
  datashield.logout(conns)


## End(Not run)

---