qp_run_plot: Plot of power estimate against the number of simulations
In qcapower: Estimate Power and Required Sample Size in QCA
Description
Usage
Arguments
Details
Value
Examples
Description
qp_run_plot allows you to plot the running power estimate to
determine whether sims is sufficiently large to derive a reliable
estimate
Usage
1
qp_run_plot(power_est, title = FALSE)
Arguments
power_est
Dataframe containing the simulation results (see
qcapower)
title
Option for adding title to plot (default FALSE)
Details
Creates a plot with ggplot2
Value
A line plot ('gg' object).
Examples
1
2
3
4
5
6
power_data <- qcapower(cases = 20, null_hypo = 0.8, alt_hypo = 0.95, sims = 10, perms = 1000)
qp_run_plot(power_data)
# Using data with 10000 estimates
data(qp_sina_data)
qp_run_plot(qp_sina_data)
qcapower documentation built on March 2, 2020, 5:09 p.m.
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Description Usage Arguments Details Value Examples
Description
qp_run_plot allows you to plot the running power estimate to
determine whether sims is sufficiently large to derive a reliable
estimate
Usage
1 | qp_run_plot(power_est, title = FALSE)
|
Arguments
power_est |
Dataframe containing the simulation results (see
|
title |
Option for adding title to plot (default |
Details
Creates a plot with ggplot2
Value
A line plot ('gg' object).
Examples
1 2 3 4 5 6 | power_data <- qcapower(cases = 20, null_hypo = 0.8, alt_hypo = 0.95, sims = 10, perms = 1000)
qp_run_plot(power_data)
# Using data with 10000 estimates
data(qp_sina_data)
qp_run_plot(qp_sina_data)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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