View source: R/mixture.overall.plot.R

mixture.overall.plot | R Documentation |

plot mixture's overall effect based on quantile of exposures

```
mixture.overall.plot(fit, data)
```

`fit` |
Fitted model from function 'plsi.lr.v1' |

`data` |
Original data set |

plot of predicted outcomes based on quantile of exposures

Yuyan Wang

```
# example to plot mixture's overall effect
data(nhanes.new)
dat <- nhanes.new
# specify variable names and parameters
Y.name <- "log.triglyceride"
X.name <- c("X1_trans.b.carotene", "X2_retinol", "X3_g.tocopherol", "X4_a.tocopherol",
"X5_PCB99", "X6_PCB156", "X7_PCB206",
"X8_3.3.4.4.5.pncb", "X9_1.2.3.4.7.8.hxcdf", "X10_2.3.4.6.7.8.hxcdf")
Z.name <- c("AGE.c", "SEX.Female", "RACE.NH.Black",
"RACE.MexicanAmerican", "RACE.OtherRace", "RACE.Hispanic" )
spline.num = 5
spline.degree = 3
initial.random.num = 1
# run PLSI linear regression
set.seed(2023)
model_1 <- plsi.lr.v1(data = dat, Y.name = Y.name, X.name = X.name, Z.name = Z.name,
spline.num, spline.degree, initial.random.num)
# plot mixture overall effect
mixture.overall.plot(model_1, dat)
```

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