summary.ictreg | R Documentation |
Function to summarize results from list experiment regression based on the ictreg() function, and to produce proportions of liars estimates.
## S3 method for class 'ictreg' summary(object, boundary.proportions = FALSE, n.draws = 10000, ...)
object |
Object of class inheriting from "ictreg" |
boundary.proportions |
A switch indicating whether, for models with
ceiling effects, floor effects, or both (indicated by the |
n.draws |
For quasi-Bayesian approximation based predictions, specify the number of Monte Carlo draws. |
... |
further arguments to be passed to or from other methods. |
predict.ictreg
produces a summary of the results from an
ictreg
object. It displays the coefficients, standard errors, and fit
statistics for any model from ictreg
.
predict.ictreg
also produces estimates of the conditional probability
of lying and of the population proportion of liars for boundary models from
ictreg()
if ceiling = TRUE
or floor = TRUE
.
The conditional probability of lying for the ceiling model is the probability that a respondent with true affirmative views of all the sensitive and non-sensitive items lies and responds negatively to the sensitive item. The conditional probability for the floor model is the probability that a respondent lies to conceal her true affirmative views of the sensitive item when she also holds true negative views of all the non-sensitive items. In both cases, the respondent may believe her privacy is not protected, so may conceal her true affirmative views of the sensitive item.
Graeme Blair, UCLA, graeme.blair@ucla.edu and Kosuke Imai, Princeton University, kimai@princeton.edu
Blair, Graeme and Kosuke Imai. (2012) “Statistical Analysis of List Experiments." Political Analysis, Vol. 20, No 1 (Winter). available at http://imai.princeton.edu/research/listP.html
Imai, Kosuke. (2011) “Multivariate Regression Analysis for the Item Count Technique.” Journal of the American Statistical Association, Vol. 106, No. 494 (June), pp. 407-416. available at http://imai.princeton.edu/research/list.html
ictreg
for model fitting
data(race) ## Not run: # Fit standard design ML model with ceiling effects # Replicates Table 7 Columns 3-4 in Blair and Imai (2012) ceiling.results <- ictreg(y ~ age + college + male + south, treat = "treat", J = 3, data = affirm, method = "ml", fit.start = "nls", ceiling = TRUE, ceiling.fit = "bayesglm", ceiling.formula = ~ age + college + male + south) # Summarize fit object and generate conditional probability # of ceiling liars the population proportion of ceiling liars, # both with standard errors. # Replicates Table 7 Columns 3-4 last row in Blair and Imai (2012) summary(ceiling.results, boundary.proportions = TRUE) ## End(Not run)
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