下面的SQL定义了一个TYPE并使用PL/R运行层次回归：
--Create TYPE to store model results
DROP TYPE IF EXISTS wj_model_results CASCADE;
CREATE TYPE wj_model_results AS (
cs text, coefext float, ci_95_lower float, ci_95_upper float,
ci_90_lower float, ci_90_upper float, ci_80_lower float,
ci_80_upper float);
--Create PL/R function to run model in R
DROP FUNCTION IF EXISTS wj_plr_RE(float [ ], text [ ]);
CREATE FUNCTION wj_plr_RE(response float [ ], cs text [ ])
RETURNS SETOF wj_model_results AS
$$
library(arm)
y<- log(response)
cs<- cs
d_temp<- data.frame(y,cs)
m0 <- lmer (y ~ 1 + (1 | cs), data=d_temp)
cs_unique<- sort(unique(cs))
n_cs_unique<- length(cs_unique)
temp_m0<- data.frame(matrix0,n_cs_unique, 7))
for (i in 1:n_cs_unique){temp_m0[i,]<-
c(exp(coef(m0)$cs[i,1] + c(0,-1.96,1.96,-1.65,1.65,
-1.28,1.28)*se.ranef(m0)$cs[i]))}
names(temp_m0)<- c("Coefest", "CI_95_Lower",
"CI_95_Upper", "CI_90_Lower", "CI_90_Upper",
"CI_80_Lower", "CI_80_Upper")
temp_m0_v2<- data.frames(cs_unique, temp_m0)
return(temp_m0_v2)
$$
LANGUAGE 'plr';
--Run modeling plr function and store model results in a
--table
DROP TABLE IF EXISTS wj_model_results_roi;
CREATE TABLE wj_model_results_roi AS SELECT *
FROM wj_plr_RE((SELECT wj_droi2_array),
(SELECT cs FROM wj_droi2_array));