Randomization in Excel

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Randomization involves assigning subjects randomly to one of two groups: one, the treatment group, which is receiving the policy intervention being evaluated, and two, the control group, which remains in status-quo/untreated. Randomizing in Excel has its advantages and disadvantages. This article gives a step-by-step guide on randomizing using Excel.

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Overview

Stata is preferred over Excel because of the following reasons:

  • Easy documentation. Randomization done in Stata can be better documented through files. Every step can be documented which makes it easier to reproduce the results.
  • Stata gives us the option of setting which version of Stata we use for randomization. This is useful when different researchers use different versions of Stata.
  • Better documentation and version control. Documentation of randomization results in Stata remains consistent across various runs.

Stata might not be available in some cases. For those cases, the advantages and disadvantages of randomizing using Excel are as follows:

Advantages: Here are some of the advantages of randomizing using Excel :

  • Balance/stratification can be achieved during randomization using Excel.
  • Simplicity. Randomization using Excel is simple to implement and produces a record.
  • Popularity. Since Excel is widely used, it is commonly understood and used by project staff.

Disadvantages: Some of the disadvantages of using Excel to randomize are as follows:

  • Transparency. Excel is more mysterious to beneficiaries than public randomization (For example - drawing names from a hat, etc)
  • Replicability. Randomization in Excel is less replicable than randomization in Stata.
  • Errors. Since the randomization involves copying and pasting, it can be subject to human errors.
  • Flexibility. It is also less flexible to changes in the randomization plan.

Steps for Randomization in Excel

Here are the steps of doing successful randomization using Excel:

  1. Randomization Rule. For example = the lowest 50% will be treatment, the rest will be assigned to control, etc.
  2. =rand(). Assign random numbers to each observation. While doing this, use "paste values" to stop recalculating the randomization.
    =rand()
  3. Sorting. Sort the random numbers from the lowest to the highest.
  4. Order. Created an ordered serial number. If you need to balance the data, then first sort by the strata, then by the random values.
  5. Assignment. Assign groups using either the mod or the if formulas.
  6. Finish. Save the record.

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