Use simple random sampling to select respondents from a list

To use the sampling tool you will need a data set with a variable of type character. Entries should be unique (i.e., no duplicates). A dataset that fits these requirements is bundled with Radiant and is available through the Data > Manage tab (i.e., choose Examples from the Load data of type drop-down and press Load). Select rndnames from the Datasets dropdown.

Names is the relevant column in this dataset and it will automatically be used as the base for sampling. Now simply choose the sample size you want and a list of names of the desired length will be created.

How does it work? Each person in the data is assigned a random number between 0 and 1 from a uniform distribution. Rows are then sorted on that random number and the \(n\) people from the list with the highest score are selected for the sample. By using a random number every respondent has the same probability of being in the sample. For example, if we need a sample of 10 people from the 100 included in the rndnames dataset each individual has a 10% chances of being included in the sample. By default, the random seed is set to 1234 to ensure the sampling results are reproducible. If there is no input in Rnd. seed the selected rows will change every time we generate a sample.

The full list of 100 people is the sampling frame. Ideally, this is a comprehensive list of all sampling units (e.g., customers or companies) in your target market.

How do you determine the appropriate value for n? Use the sample size tools in the Design menu.

Report > Rmd

Add code to Report > Rmd to (re)create the sample by clicking the icon on the bottom left of your screen or by pressing ALT-enter on your keyboard.


For an overview of related R-functions used by Radiant for sampling and sample size calculations see Design > Sample

© Vincent Nijs (2018) Creative Commons License