| Type: | Package | 
| Title: | Calculates Critical Test Statistics to Control False Discovery Rates in Marginal Effects Plots | 
| Version: | 1.2 | 
| Date: | 2019-6-6 | 
| Author: | Justin Esarey and Jane Lawrence Sumner | 
| Maintainer: | Justin Esarey <justin@justinesarey.com> | 
| Description: | Implements the procedures suggested in Esarey and Sumner (2017) http://justinesarey.com/interaction-overconfidence.pdf for controlling the false discovery rate when constructing marginal effects plots for models with interaction terms. | 
| Depends: | stats, R (≥ 3.4) | 
| License: | GPL-2 | GPL-3 [expanded from: GPL] | 
| LazyData: | true | 
| RoxygenNote: | 6.1.1 | 
| Encoding: | UTF-8 | 
| NeedsCompilation: | no | 
| Packaged: | 2019-06-06 19:47:51 UTC; justi | 
| Repository: | CRAN | 
| Date/Publication: | 2019-06-06 21:00:03 UTC | 
Bootstrapping t-statistics
Description
This function is defunct.
Usage
bootFun(...)
Arguments
| ... | Any argument to the function (ignored). | 
References
Esarey, Justin, and Jane Lawrence Sumner. 2018. "Corrigendum to 'Marginal Effects in Interaction Models: Determining and Controlling the False Positive Rate.'"
Critical t-statistic
Description
This function calculates the critical t-statistic to limit the false discovery rate (Benjamini and Hochberg 1995) for a marginal effects plot to a specified level.
Usage
fdrInteraction(me.vec, me.sd.vec, df, type = "BH", level = 0.95)
Arguments
| me.vec | A vector of marginal effects. | 
| me.sd.vec | A vector of standard deviations for the marginal effects. | 
| df | Degrees of freedom. | 
| type | Should the BH (Benjamini and Hochberg 1999) or BY (Benjamini and Yekutieli 2000) correction be used? Options are "BH" (the default) or "BY". | 
| level | The level of confidence. Defaults to 0.95. | 
Value
The critical t-statistic for the interaction.
Author(s)
Justin Esarey and Jane Lawrence Sumner
References
Benjamini, Yoav, and Yosef Hochberg. 1995. "Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing." Journal of the Royal Statistical Society, Series B 57(1): 289-300.
Benjamini, Yoav, and Daniel Yekutieli. 2001. "The Control of the False Discovery Rate in Multiple Testing Under Dependency." The Annals of Statistics 29(4): 1165-1188.
Clark, William R., and Matt Golder. 2006. "Rehabilitating Duverger's Theory." Comparative Political Studies 39(6): 679-708.
Esarey, Justin, and Jane Lawrence Sumner. 2017. "Marginal Effects in Interaction Models: Determining and Controlling the False Positive Rate." Comparative Political Studies 51(9): 1144-1176.
Esarey, Justin, and Jane Lawrence Sumner. 2018. "Corrigendum to 'Marginal Effects in Interaction Models: Determining and Controlling the False Positive Rate.'"
Examples
## Not run:  
data(legfig)                # Clark and Golder 2006 replication data
# limit to established democracies from the 1990s
dat<-subset(legfig, subset=(nineties==1 & old==1))
lin.mod <- lm(enep1 ~ eneg + logmag + logmag_eneg + uppertier_eneg + uppertier +
proximity1 + proximity1_enpres + enpres, data=dat)
# save betas
beta.mod <- coefficients(lin.mod)
# save vcv
vcv.mod <- vcov(lin.mod)
# calculate MEs
mag <- seq(from=0.01, to=5, by=0.01)
me.vec <- beta.mod[2] + beta.mod[4]*mag
me.se <- sqrt( vcv.mod[2,2] + (mag^2)*vcv.mod[4,4] + 2*(mag)*(vcv.mod[2,4]) )
ci.hi <- me.vec + 1.697 * me.se
ci.lo <- me.vec - 1.697 * me.se
plot(me.vec ~ mag, type="l", ylim = c(-4, 6))
lines(ci.hi ~ mag, lty=2)
lines(ci.lo ~ mag, lty=2)
fdrInteraction(me.vec, me.se, df=lin.mod$df, level=0.90)                  # 4.233986
ci.hi <- me.vec + 4.233986 * me.se
ci.lo <- me.vec - 4.233986 * me.se
lines(ci.hi ~ mag, lty=2, lwd=2)
lines(ci.lo ~ mag, lty=2, lwd=2)
abline(h=0, lty=1, col="gray")
legend("topleft", lwd=c(1,2), lty=c(1,2), legend=c("90% CI", "90% FDR CI"))
## End(Not run)
Determine Critical t-Statistic For Marginal Effects Plot
Description
This function is defunct.
Usage
findMultiLims(...)
Arguments
| ... | Any argument to the function (ignored). | 
References
Esarey, Justin, and Jane Lawrence Sumner. 2018. "Corrigendum to 'Marginal Effects in Interaction Models: Determining and Controlling the False Positive Rate.'"
Replication data for Clark and Golder (2006)
Description
District magnitude and ethnic heterogeneity data from a pooled sample of established democracies in the 1990s. Data originally from Clark and Golder (2006).
Format
A data frame with 754 rows and 33 variables:
- country
- country name 
- countrynumber
- country number 
- year
- year of observation 
- enep1
- electoral parties 
- eneg
- ethnic heterogeneity 
- logmag
- district magnitude 
- legelec
- legislative election 
- preselec
- presidential election 
- regime
- regime as of 31 Dec of given year (0=democracy, 1=dictatorship) 
- regime_leg
- regime type at time of leg. election (0=democracy, 1=dictatorship) 
- eighties
- election in 1980s closest to 1985 
- nineties
- election in 1990s closest to 1995 
- old
- elections in countries that did not transition to democracy in 1990s 
- avemag
- average district magnitude 
- districts
- number of electoral districts 
- enep
- effective number of ethnic groups fearon 
- enep_others
- n/a 
- enpp
- parliamentary parties - uncorrected 
- enpp_others
- n/a 
- enpp1
- parliamentary parties - corrected 
- enpres
- effective number of presidential candidates 
- medmag
- median district magnitude 
- newdem
- first election of new democracy 
- proximity1
- proximity - continuous 
- proximity2
- proximity - dichotomous 
- seats
- assembly size 
- upperseats
- number of upper tier seats 
- uppertier
- percentage of uppertier seats 
- uppertier_eneg
- uppertier*eneg 
- logmag_eneg
- logmag*eneg 
- proximity1_enpres
- proximity1*enpres 
- twoelections
- n/a 
- twoelections1
- n/a 
...
Source
Clark, William R., and Matt Golder. 2006. "Rehabilitating Duverger's Theory." Comparative Political Studies 39(6): 679-708.