EenieMeenie

Decides to which experimental group a member of a population should be assigned.

Installation

EenieMeenie is a Ruby gem, and can be installed using gem install eenie_meenie or by adding the following to your application's Gemfile:

gem 'eenie_meenie', '0.1.1'

Usage

Attention! The usage of EeenieMeenie::Assignment changed with the release of version 0.1.0. With the new algorithm you'll be able to:

1. Assign a threshold (a Float to represent percentage) to each experimental group.
2. Assign a threshold of "DO NOT CARE" to any group by passing false instead of a Float
3. Tell EeenieMeenie which groups can be assigned by the algorithm. Any group with a threshold should be included here.
4. Tell it how to scope the member class (tell it which study, if you're using one member class for all studies)
5. Specify the population to be used when calculating whether a group's population threshold has been reached.

Example Configurations

eenie_meenie users can specify the population using the :members option, e.g.

EenieMeenie::Assignment.new({
  member:  @some_member,
  members: MemberClass.where(something).joins(another),
  groups:  ["Experimental", "Control"],
  group_rules: {
    "Experimental" => { threshold: 0.51 },
    "Control"      => { threshold: 0.51 }
  }
})

Other examples ...

# Control: Do not care  (chosen manually, if ever)
# Experimental A: %50   (randomly assign)
# Experimental B: %50   (randomly assign)

EenieMeenie::Assignment.new({
  groups: ["Experimental A", "Experimental B"],  # EenieMeenie's assignment options
  member: @obj,                                  # Member of population
  group_rules: {
    "Control"        => { threshold: false },    # Don't care
    "Experimental A" => { threshold: 0.5 },      # No more than 50%
    "Experimental B" => { threshold: 0.5 }       # No more than 50%
  },
  class_rules: { organization_id: 1}             # Only consider members belonging to Organization 1
}).execute!

# Control:        %33.3   (randomly assign)
# Experimental A: %33.3   (randomly assign)
# Experimental B: %33.3   (randomly assign)

EenieMeenie::Assignment.new({
  groups: ["Control", "Experimental A", "Experimental B"], # EenieMeenie's assignment options
  member: @obj,                                            # Member of population
  group_rules: {
    "Control"         => { threshold: (1.0 / 3.0) },       # No more than one-third
    "Experimental A"  => { threshold: (1.0 / 3.0) },       # No more than one-third
    "Experimental B" => { threshold:  (1.0 / 3.0) }        # No more than one-third
  },
  class_rules: { organization_id: 1} # Only consider members belonging to Organization 1
}).execute!

# Control:        %50         (randomly assign)
# Experimental:   %50         (randomly assign)
# Experimental A: Do not care (manually assign)
# Experimental B: Do not care (manually assign)

# If "Control" is too full, put them in "Experimental"          ...
# Later someone will choose whether they're in "Experimental A" ...
# or in "Experimental B"

EenieMeenie::Assignment.new({
  groups: ["Control", "Experimental"],       # EenieMeenie's assignment options
  member: @obj,                              # Member of population
  group_rules: {
    "Control"        => { threshold: 0.5 },   # No more than one half
    "Experimental"   => { threshold: 0.5 },   # No more than one half
    "Experimental A" => { threshold: false }  # Don't care
    "Experimental B" => { threshold: false }  # Don't care
  }
}).execute!

Pull requests/issues

Please submit any useful pull requests through GitHub. Please report any bugs using Github's issue tracker.