Nothing
# install the package and use this script to test the package
library("APCI")
# or: remotes::install_github("jiahui1902/APCI")
test_data <- APCI::women9017
test_data$acc <- as.factor(test_data$acc)
test_data$pcc <- as.factor(test_data$pcc)
test_data$educc <- as.factor(test_data$educc)
test_data$educr <- as.factor(test_data$educr)
# equal age and period interval
APC_I <- APCI::apci(outcome = "inlfc",
age = "acc",
period = "pcc",
cohort = "ccc",
weight = "wt",
data = test_data,dev.test=FALSE,
print = TRUE,
family = "gaussian")
summary(APC_I)
APC_I$model$coefficients
summary(APC_I$model)
APC_I$dev_global
APC_I$dev_local
APC_I$intercept
APC_I$age_effect
APC_I$period_effect
APC_I$cohort_average
APC_I$cohort_slope
APC_I$cohort_index
apci.plot.raw(data = test_data, outcome_var = "inlfc",age="acc",period="pcc")
apci.plot(data = test_data, outcome_var = "inlfc", age = "acc",model=APC_I,
period = "pcc",type="explore")
apci.bar(model = APC_I, age = "acc",period = "pcc")
apci.plot.heatmap(model = APC_I, age = "acc",period = "pcc")
apci.plot.hexagram(model = APC_I, age = "acc",period = "pcc",
first_age = 20,first_period = 1990,interval = 5)
apci.plot(data = test_data, outcome_var = "inlfc", age = "acc",model=APC_I,
period = "pcc")
# other type of generalized linear model
APC_I2 <- APCI::apci(outcome = "inlfc",
age = "acc",
period = "pcc",
cohort = "ccc",
weight = "wt",
covariate = "offset(log(educ))",
data = test_data,dev.test=FALSE,
print = TRUE,
family = "poisson")
summary(APC_I2)
# unequal age and period interval
uneqal_interval1 <- APCI::apci(outcome = "inlfc",
age = "age",
period = "year",
cohort = "ccc",
weight = "wt",
data = test_data,dev.test=FALSE,
print = TRUE,
family = "gaussian",
unequal_interval = TRUE,
age_range = 20:64,
period_range = 1990:2019,
age_interval = 5,
period_interval = 10)
uneqal_interval1$cohort_index
uneqal_interval2 <- APCI::apci(outcome = "inlfc",
age = "age",
period = "year",
cohort = "ccc",
weight = "wt",
data = test_data,dev.test=FALSE,
print = TRUE,
family = "gaussian",
unequal_interval = TRUE,
age_range = 20:64,
period_range = 1990:2019,
age_interval = 10,
period_interval = 5)
uneqal_interval2$cohort_index
uneqal_interval3 <- APCI::apci(outcome = "inlfc",
age = "age",
period = "year",
cohort = "ccc",
weight = "wt",
data = test_data,dev.test=FALSE,
print = TRUE,
family = "gaussian",
unequal_interval = T,
age_range = 20:69,
period_range = 1990:2019,
age_group = c("20-29","30-39",
"40-49","50-59",
"60-69"),
period_group = c("1990-1994","1995-1999",
"2000-2004","2005-2009",
"2010-2014","2015-2019"))
uneqal_interval3$cohort_index
uneqal_interval2$cohort_index
uneqal_interval3$cohort_index
uneqal_interval2$cohort_average$cohort_average
uneqal_interval3$cohort_average$cohort_average
# simulated panel data for GEE
simulation_gee <- simulation
simulation_gee$id <- 1:nrow(simulation_gee)
simulation_gee$idid <- 1:nrow(simulation_gee)
# simulation_gee$id <- NULL
simulation_gee = simulation_gee[sample(nrow(simulation_gee),30000,replace=T),]
model_gee <- apci(outcome = "y",
age = "age",
period = "period",
cohort = NULL,
weight = NULL,
covariate = NULL,
data=simulation_gee,
family ="gaussian",
dev.test = FALSE,
print = TRUE,
gee = TRUE,
id = "id",
corstr = "exchangeable")
summary(model_gee)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.