Difference between revisions of "Randomization in Excel"

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[[Randomization | 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.  
[[Randomization | Randomization]] involves assigning subjects randomly to one of two groups: the '''treatment group''', which is receiving the policy intervention being evaluated, and the '''control group''' which is untreated. '''Randomizing in Excel''' has its advantages and disadvantages. This article gives a step-by-step guide on randomizing using Excel.  
   
   
== Read First ==
== Read First ==
*[[Randomized Evaluations: Principles of Study Design | Randomized Evaluations]] are field experiments that use [[Randomization | randomization]] to determine the effectiveness of an intervention.
*[[Randomized Evaluations: Principles of Study Design | Randomized Evaluations]] are field experiments that use [[Randomization | randomization]] to determine the effectiveness of an intervention.
* If [[Randomization in Stata | randomization using Stata]] is feasible, then it should always be the preferred option as[[Randomization in Stata | randomization in Stata]] is more easily [[Reproducible Research | reproducible]].
* If [[Randomization in Stata | randomization using Stata]] is feasible, then it should always be the preferred option as it is more easily [[Reproducible Research | reproducible]].
* [[Randomization | Randomization]] can also be done using [[SurveyCTO Programming | SurveyCTO]] however, [[Stata Coding Practices |Stata]] is the preferred option over '''SurveyCTO'''.
* '''Randomization''' can also be done [[Randomization in SurveyCTO | using SurveyCTO]]. However, [[Stata Coding Practices |Stata]] is the preferred option over '''SurveyCTO'''.
* [[Sampling | Sampling]] is the process of randomly selecting [[Units of Observation|units]] from a population of interest to represent the characteristics of that population and is crucial to conducting [[Randomized Control Trials| randomized experiments]] when deciding the effectiveness of an intervention.
* [[Sampling | Sampling]] is the process of '''randomly''' selecting [[Units of Observation|units]] from a population of interest to represent the characteristics of that population and is crucial to conducting '''randomized experiments''' when deciding the effectiveness of an intervention.


== Overview ==
== Overview ==
[[Randomization in Stata | Stata]] is preferred over Excel because of the following reasons:
[[Randomization in Stata | Stata]] is preferred over Excel because of the following reasons:
* '''Easy documentation.''' [[Randomization | Randomization]] done in [[Randomization in Stata | Stata]] can be better documented through files. Every step can be documented which makes it easier to [[Reproducible Research#Replication and Reproducibility |reproduce]] the results.  
* '''Easy documentation.''' [[Randomization | Randomization]] done in [[Randomization in Stata | Stata]] can be better documented through files. Every step can be documented which makes it easier to [[Reproducible Research#Replication and Reproducibility |reproduce]] the results.  

Revision as of 19:07, 8 August 2023

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

Read First

  • Randomized Evaluations are field experiments that use randomization to determine the effectiveness of an intervention.
  • If randomization using Stata is feasible, then it should always be the preferred option as it is more easily reproducible.
  • Randomization can also be done using SurveyCTO. However, Stata is the preferred option over SurveyCTO.
  • Sampling is the process of randomly selecting units from a population of interest to represent the characteristics of that population and is crucial to conducting randomized experiments when deciding the effectiveness of an intervention.

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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