ImitSim: Simulation of Imitation by Bureaucrrats

Description Usage Arguments Details Value Note Author(s) References Examples

View source: R/ImitSim.R

Description

ImitSim() runs an R version of the imitation simulation as published in Working, Shirking, and Sabotage (1997). The original function was written in APL11, which hardly anyone uses. This is the core function for the simulation in the book.

Usage

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ImitSim(replications, NumBur, MaxIter, supervision, omniscient, posprefs, binary, Tolerance, Std,
Punishment, SupObsParms, PrefParms, RespParms, BurObsParms)

Arguments

replications

Number (integer) of replications of each run.

NumBur

Number (integer) of Bureaucrats.

MaxIter

Number (integer) of iterations for each replication to run.

supervision

"Relative" (default) for supervisor to identify deviants based on low-end deviations from responses by other bureaucrats, "Fixed" for the supervisor to identify deviants based on a floor of minimal performance.

omniscient

Logical, FALSE (default) if the supervisor cannot see everyone, TRUE if she can.

posprefs

Logical, FALSE (default) if the preferences of the bureaucrats are not constrained to be positive. TRUE if the preferences of the bureacrats must be positive.

binary

TRUE (default) if the observability matrix is converted to binary for the connectivvity calculations. Throws an error otherwise.

Tolerance

Number (float) of standard deviations away from mean that the supervisor will regard as being deviant. Only makes sense if the "supervision is "Relative".

Std

Number (float) in range (-1,1) for supervisor to regard as the floor for performance. Only makes sense if the supervision is "Fixed".

Punishment

Number (float) subtracted from each deviant bureaucrat.

SupObsParms

Vector (mean,sd) for the observability of the supervisor. Can be redunddant with omniscient, which sets all bureaucrats as visiible (i.e., equivalent to SupObsPamrs=c(1,0)

PrefParms

Vector (mean,sd) for the preferences of the bureaucrat.

RespParms

Vector (mean,sd) for the responses of the bureaucrats.

BurobsParms

Vector (mean,sd) for the observability of each bureaucrat to one another.

debug

If TRUE, prints debugging information.

quiet

If TRUE, prints no startup information (but will print debugging information, if requested).

Details

This might be the place for text about the way the function will work.

Value

ExecSummary

Returns a (tidy-ready) dataframe that contains: Replication, Iteration, SupUtilMean, SupUtilSD, PrefMean, PrefSD, ResponseMean, ResponseSD, SupObsMean, SupObsSD, BurObsMean, BurObsSD, Tolerance (or Std), Punishment, Connectivity, FinalResponseMean, FinalResponseSD, BurUtilMean, BurUtilSD

version

1.1b3

NumBurs

Number of bureaucrats (default=10)

MaxIter

Number of iterations per replication (default=10)

binary

Whether the connectivity of the observability is computed using a binary adjacency matrix.

supervision

The mode of supervision ("Relative", "Fixed")

posprefs

Are the preferences constrained to be positive?

omniscient

Is the supervisor omniscient? (I.e., can see performance of all her subordinates?)

Performance

Matrix of performance of each bureaucrat in each iteration of every replication, (Replications*MaxIter*Numbers) x (replication, iteration, (vector of responses)))

ObstyRecord

Matrix of observability for each replication, (MaxIter*Numburs) x Numburss)

SeenRecord

Matrix of observability of each bureaucrat by supervisor in each iteration of every replication, (Replication*MaxIter*NumBurs) x (replication, iteration, (vector of seen bureaucrats))

Note

Makes use of the igraph library. You should have it installed.

Author(s)

John Brehm

References

Brehm, John and Scott Gates. 1997. Working, Shirking, and Sabotage. Ann Arbor, MI

Examples

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# To replicate Table 3.1 with relative supervision, allowing for preferences to be (-1,1)
wss <- ImitSim(1000)
hist(wss$ExecSummary$SupUtilMean)

jjbrehm/BadApple documentation built on Aug. 1, 2020, 12:54 p.m.