Created
January 13, 2019 20:38
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Submission for 2017 EM:IP Cover Showcase
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### Define functions ----------------------------------------------------------- | |
logit <- function(x) { | |
exp(x) / (1 + exp(x)) | |
} | |
comp <- function(x, y, a1 = 1, a2 = 1, d = 0, c = 0) { | |
lin_comb <- (a1 * x) + (a2 * y) | |
c + (1 - c) * logit(lin_comb - d) | |
} | |
noncomp <- function(x, y, a1 = 1, a2 = 1, d1 = 0, d2 = 0, c = 0) { | |
c + (1 - c) * prod(logit((a1 * x) - d1), logit((a2 * y) - d2)) | |
} | |
partcomp <- function(x, y, a1 = 1, a2 = 1, a3 = 0.3, d = 0, c = 0) { | |
c + (1 - c) * logit((a1 * x) + (a2 * y) + (a3 * x * y) - d) | |
} | |
### Generate data -------------------------------------------------------------- | |
theta_1 <- seq(-3, 3, 0.01) | |
theta_2 <- seq(-3, 3, 0.01) | |
pl1 <- crossing(theta_1, theta_2) %>% | |
mutate( | |
Model = "1PL", | |
Compensatory = map2_dbl(.x = theta_1, .y = theta_2, .f = comp), | |
Noncompensatory = map2_dbl(.x = theta_1, .y = theta_2, .f = noncomp), | |
Partial = map2_dbl(.x = theta_1, .y = theta_2, .f = partcomp, a3 = 0.3) | |
) | |
pl2 <- crossing(theta_1, theta_2) %>% | |
mutate( | |
Model = "2PL", | |
Compensatory = map2_dbl(.x = theta_1, .y = theta_2, .f = comp, | |
a1 = 0.8, a2 = 1.8), | |
Noncompensatory = map2_dbl(.x = theta_1, .y = theta_2, .f = noncomp, | |
a1 = 0.8, a2 = 1.8), | |
Partial = map2_dbl(.x = theta_1, .y = theta_2, .f = partcomp, | |
a1 = 0.8, a2 = 1.8, a3 = 0.3) | |
) | |
pl3 <- crossing(theta_1, theta_2) %>% | |
mutate( | |
Model = "3PL", | |
Compensatory = map2_dbl(.x = theta_1, .y = theta_2, .f = comp, | |
a1 = 0.8, a2 = 1.8, c = 0.2), | |
Noncompensatory = map2_dbl(.x = theta_1, .y = theta_2, .f = noncomp, | |
a1 = 0.8, a2 = 1.8, c = 0.2), | |
Partial = map2_dbl(.x = theta_1, .y = theta_2, .f = partcomp, | |
a1 = 0.8, a2 = 1.8, a3 = 0.3, c = 0.2) | |
) | |
### Create plot ---------------------------------------------------------------- | |
bind_rows(pl1, pl2, pl3) %>% | |
gather(Method, Probability, Compensatory:Partial) %>% | |
mutate(Method = factor(Method, levels = c("Compensatory", "Partial", | |
"Noncompensatory"), labels = c("Compensatory", "Partially Compensatory", | |
"Noncompensatory"))) %>% | |
ggplot(mapping = aes(x = theta_1, y = theta_2)) + | |
facet_grid(Model ~ Method) + | |
geom_raster(aes(fill = Probability), interpolate = TRUE) + | |
geom_contour(aes(z = Probability), color = "black", binwidth = 0.1) + | |
scale_x_continuous(breaks = seq(-10, 10, 1)) + | |
scale_y_continuous(breaks = seq(-10, 10, 1)) + | |
scale_fill_distiller(name = "Probability of Correct Response", | |
palette = "Spectral", direction = -1, limits = c(0, 1), | |
breaks = seq(0, 1, 0.1)) + | |
labs(x = expression(paste(theta[1])), y = expression(paste(theta[2]))) + | |
theme_minimal() + | |
theme( | |
aspect.ratio = 1, | |
legend.position = "bottom", | |
legend.title = element_text(vjust = 0.5, size = 14), | |
legend.text = element_text(size = 12), | |
axis.text = element_text(size = 12), | |
axis.title = element_text(size = 14), | |
strip.text = element_text(face = "bold", size = 14), | |
legend.key.width = unit(1, "inches") | |
) + | |
guides(fill = guide_colorbar(title.position = "top", title.hjust = 0.5)) |
Author
wjakethompson
commented
Jan 13, 2019
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