Title: | Bayesian Distributed Lag Interaction Models |
Version: | 0.5.0 |
Date: | 2025-06-09 |
Description: | Estimation and interpretation of Bayesian distributed lag interaction models (BDLIMs). A BDLIM regresses a scalar outcome on repeated measures of exposure and allows for modification by a categorical variable under four specific patterns of modification. The main function is bdlim(). There are also summary and plotting files. Details on methodology are described in Wilson et al. (2017) <doi:10.1093/biostatistics/kxx002>. |
License: | GPL (≥ 3) |
Encoding: | UTF-8 |
Imports: | LaplacesDemon, ggplot2, parallel, BayesLogit |
RoxygenNote: | 7.3.2 |
BugReports: | https://github.com/anderwilson/bdlim/issues/ |
URL: | https://anderwilson.github.io/bdlim/, https://github.com/AnderWilson/bdlim/ |
Depends: | R (≥ 2.10) |
LazyData: | true |
NeedsCompilation: | no |
Packaged: | 2025-06-10 22:16:40 UTC; anderwilson |
Author: | Ander Wilson |
Maintainer: | Ander Wilson <ander.wilson@colostate.edu> |
Repository: | CRAN |
Date/Publication: | 2025-06-11 03:00:02 UTC |
bdlim: Bayesian Distributed Lag Interaction Models
Description
Estimation and interpretation of Bayesian distributed lag interaction models (BDLIMs). A BDLIM regresses a scalar outcome on repeated measures of exposure and allows for modification by a categorical variable under four specific patterns of modification. The main function is bdlim(). There are also summary and plotting files. Details on methodology are described in Wilson et al. (2017) doi:10.1093/biostatistics/kxx002.
Details
The main function is bdlim4
.
Author(s)
Maintainer: Ander Wilson ander.wilson@colostate.edu (ORCID)
References
Wilson A, Chiu YM, Hsu HL, Wright RO, Wright RJ, Coull BA (2017). “Bayesian distributed lag interaction models to identify perinatal windows of vulnerability in children's health.” Biostatistics, 18(3), 537–552. doi:10.1093/biostatistics/kxx002. arXiv preprint.
See Also
Useful links:
Report bugs at https://github.com/anderwilson/bdlim/issues/
Fit the BDLIM model with 1 pattern of modification
Description
Fit the BDLIM model with 1 pattern of modification
Usage
bdlim1(
y,
exposure,
covars,
group,
id = NULL,
w_free,
b_free,
df,
nits,
nburn = round(nits/2),
nthin = 1,
progress = TRUE
)
Arguments
y |
A vector of outcomes |
exposure |
A matrix of exposures with one row for each individual |
covars |
A matrix or data.frame of covariates This should not include the grouping factor (see group below). This may include factor variables. |
group |
A vector of group memberships. This should be a factor variable. |
id |
An optional vector of individual IDs if there are repeated measures or other groupings that a random intercept should be included for. This must be a factor variable. |
w_free |
Logical indicating if the weight functions are shared by all groups (FALSE) or group-specific (TRUE). |
b_free |
Logical indicating if the effect sizes are shared by all groups (FALSE) or group-specific (TRUE). |
df |
Degrees of freedom for the weight functions |
nits |
Number of MCMC iterations. |
nburn |
Number of MCMC iterations to be discarded as burn in. The default is half if the MCMC iterations. This is only used for WAIC in this function but is passed to summary and plot functions and used there. |
nthin |
Thinning factors for the MCMC. This is only used for WAIC in this function but is passed to summary and plot functions and used there. |
progress |
Logical indicating if a progress bar should be shown during MCMC iterations. Default is TRUE. |
Value
A list with posteriors of parameters
Examples
# run BDLIM with modification by ChildSex
fit_sex <- bdlim1(
y = sbd_bdlim$bwgaz,
exposure = sbd_bdlim[,paste0("pm25_",1:37)],
covars = sbd_bdlim[,c("MomPriorBMI","MomAge","race","Hispanic",
"EstMonthConcept","EstYearConcept")],
group = as.factor(sbd_bdlim$ChildSex),
w_free = TRUE,
b_free = TRUE,
df = 5,
nits = 5000
)
# show model fit results
fit_sex
#summarize results
sfit_sex <- summary(fit_sex)
sfit_sex
# graph the estimated distributed lag functions for each group
plot(sfit_sex)
# run BDLIM with no modification
# here a single group is put in for group
# the group must be a factor
# w_free and b_free must be FALSE because modification is not allowed with only one group
fit_onegroup <- bdlim1(
y = sbd_bdlim$bwgaz,
exposure = sbd_bdlim[,paste0("pm25_",1:37)],
covars = sbd_bdlim[,c("MomPriorBMI","MomAge","race","Hispanic",
"EstMonthConcept","EstYearConcept")],
group = as.factor(rep("A",nrow(sbd_bdlim))),
w_free = FALSE,
b_free = FALSE,
df = 5,
nits = 5000
)
# show model fit results
fit_onegroup
#summarize results
sfit_onegroup <- summary(fit_onegroup)
sfit_onegroup
# graph the estimated distributed lag functions for the one group
plot(sfit_onegroup)
# extract the weight function
getw(fit_onegroup)
Fit the BDLIM model with 1 pattern of modification with logistic regression
Description
Fit the BDLIM model with 1 pattern of modification with logistic regression
Usage
bdlim1_logistic(
y,
exposure,
covars,
group,
id = NULL,
w_free,
b_free,
df,
nits,
nburn = round(nits/2),
nthin = 1,
progress = TRUE
)
Arguments
y |
A vector of binary outcomes |
exposure |
A matrix of exposures with one row for each individual |
covars |
A matrix or data.frame of covariates This should not include the grouping factor (see group below). This may include factor variables. |
group |
A vector of group memberships. This should be a factor variable. |
id |
An optional vector of individual IDs if there are repeated measures or other groupings that a random intercept should be included for. This must be a factor variable. |
w_free |
Logical indicating if the weight functions are shared by all groups (FALSE) or group-specific (TRUE). |
b_free |
Logical indicating if the effect sizes are shared by all groups (FALSE) or group-specific (TRUE). |
df |
Degrees of freedom for the weight functions |
nits |
Number of MCMC iterations. |
nburn |
Number of MCMC iterations to be discarded as burn in. The default is half if the MCMC iterations. This is only used for WAIC in this function but is passed to summary and plot functions and used there. |
nthin |
Thinning factors for the MCMC. This is only used for WAIC in this function but is passed to summary and plot functions and used there. |
progress |
Logical indicating if a progress bar should be shown during MCMC iterations. Default is TRUE. |
Value
A list with posteriors of parameters
Fit the BDLIM model with all 4 patterns of modification
Description
Fit the BDLIM model with all 4 patterns of modification
Usage
bdlim4(
y,
exposure,
covars,
group,
id = NULL,
df,
nits,
nburn = round(nits/2),
nthin = 1,
parallel = FALSE,
family = "gaussian"
)
Arguments
y |
A vector of outcomes |
exposure |
A matrix of exposures with one row for each individual |
covars |
A matrix or data.frame of covariates This should not include the grouping factor (see group below). This may include factor variables. |
group |
A vector of group memberships. This should be a factor variable. |
id |
An optional vector of individual IDs if there are repeated measures or other groupings that a random intercept should be included for. This must be a factor variable. |
df |
Degrees of freedom for the weight functions |
nits |
Number of MCMC iterations. |
nburn |
Number of MCMC iterations to be discarded as burn in. The default is half if the MCMC iterations. This is only used for WAIC in this function but is passed to summary and plot functions and used there. |
nthin |
Thinning factors for the MCMC. This is only used for WAIC in this function but is passed to summary and plot functions and used there. |
parallel |
Logical to use parallel computing for 4 models. If TRUE then the min of 4 and number of cores available will be used. |
family |
Family of model to be used. Supported options are "gaussian" for a normal/Gaussian linear model and "binomial" for a logistic model. |
Value
A list of results from each different pattern of modification and model compassion metrics
Examples
# run BDLIM with modification by ChildSex
fit_sex <- bdlim4(
y = sbd_bdlim$bwgaz,
exposure = sbd_bdlim[,paste0("pm25_",1:37)],
covars = sbd_bdlim[,c("MomPriorBMI","MomAge","race","Hispanic",
"EstMonthConcept","EstYearConcept")],
group = as.factor(sbd_bdlim$ChildSex),
df = 5,
nits = 5000,
parallel = FALSE
)
# show model comparison results
fit_sex
#summarize results
sfit_sex <- summary(fit_sex)
sfit_sex
# graph the estimated distributed lag functions for each group
plot(sfit_sex)
Get weight function
Description
Get weight function
Usage
getw(object, type = "normal", ...)
Arguments
object |
An object of class bdlim1. |
type |
Type of summary. The default is 'normal' which returns a summary with the mean projected to conform with the norm 1 constraint. Others are |
... |
Not used. |
Value
A data frame with either the summary of the weight function (types normal and raw) or a posterior sample of the weight function (type full).
Make orthonomal basis for weight functions
Description
Make orthonomal basis for weight functions
Usage
makebasis(exposure, df)
Arguments
exposure |
Matrix of repeated measures of exposure that is n x T where n is the number of observations and T is the number of time points. |
df |
Degrees of freedom (including intercept) for the natural spline basis to be used. |
Value
A matrix with orthonormal basis expansions of exposure time. The matrix is T x df. These have the span of natural splines with an intercept and df degrees of freedom.
Examples
B <- makebasis(sbd_bdlim[,paste0("pm25_",1:37)], df=4)
Model comparison for bdlim objects
Description
Model comparison for bdlim objects
Usage
modelcompare(object)
Arguments
object |
An object of class bdlim4 obtained from the bdlim4 function. |
Value
A vector of model probabilities.
Plot for Summary of BDLIM (summary.bdlim1 version)
Description
Plot for Summary of BDLIM (summary.bdlim1 version)
Usage
## S3 method for class 'summary.bdlim1'
plot(x, ...)
Arguments
x |
An object of class summary.bdlim1. |
... |
Not used. |
Value
An ggplot2 figure.
Examples
# run BDLIM with modification by ChildSex
fit_sex <- bdlim4(
y = sbd_bdlim$bwgaz,
exposure = sbd_bdlim[,paste0("pm25_",1:37)],
covars = sbd_bdlim[,c("MomPriorBMI","MomAge","race","Hispanic",
"EstMonthConcept","EstYearConcept")],
group = as.factor(sbd_bdlim$ChildSex),
df = 5,
nits = 5000,
parallel = FALSE
)
# show model comparison results
fit_sex
#summarize results
sfit_sex <- summary(fit_sex)
# graph the estimated distributed lag functions for each group
plot(sfit_sex)
# can save plot as an object and modify with ggplot2
library(ggplot2)
plt <- plot(sfit_sex)
plt + ggtitle("My plot with BDLIM") +
ylab("Estimated expected difference in\nBWGAZ per 1 ug/m3 increase in exposure")
# the summary file has the data to make this plot
head(sfit_sex$dlfun)
Plot for Summary of BDLIM
Description
Plot for Summary of BDLIM
Usage
## S3 method for class 'summary.bdlim4'
plot(x, ...)
Arguments
x |
An object of class summary.bdlim4. |
... |
Not used. |
Value
An ggplot2 figure.
Examples
# run BDLIM with modification by ChildSex
fit_sex <- bdlim4(
y = sbd_bdlim$bwgaz,
exposure = sbd_bdlim[,paste0("pm25_",1:37)],
covars = sbd_bdlim[,c("MomPriorBMI","MomAge","race","Hispanic",
"EstMonthConcept","EstYearConcept")],
group = as.factor(sbd_bdlim$ChildSex),
df = 5,
nits = 5000,
parallel = FALSE
)
# show model comparison results
fit_sex
#summarize results
sfit_sex <- summary(fit_sex)
# graph the estimated distributed lag functions for each group
plot(sfit_sex)
# can save plot as an object and modify with ggplot2
library(ggplot2)
plt <- plot(sfit_sex)
plt + ggtitle("My plot with BDLIM") +
ylab("Estimated expected difference in\nBWGAZ per 1 ug/m3 increase in exposure")
# the summary file has the data to make this plot
head(sfit_sex$dlfun)
Print Results
Description
Print Results
Usage
## S3 method for class 'bdlim1'
print(x, ...)
Arguments
x |
An object of class bdlim1. |
... |
Not used. |
Value
Assorted model output.
Print Results
Description
Print Results
Usage
## S3 method for class 'bdlim4'
print(x, ...)
Arguments
x |
An object of class bdlim4. |
... |
Not used. |
Value
Assorted model output.
Print Summary of bdlim4
Description
Print Summary of bdlim4
Usage
## S3 method for class 'summary.bdlim4'
print(x, ...)
Arguments
x |
An object of class summary.bdlim4. |
... |
Not used. |
Value
Assorted model output.
Simulated Birth Data
Description
A dataset containing simulated birth data for examples with bdlim. Add outcome and covariate data is simulated. The exposure data is real exposure data. Therefore, it has realistic correlation structure. The exposures are consistent with the date of conception variables. Each exposure is scaled by its IQR.
Usage
sbd_bdlim
Format
A data frame with 1000 rows (observations) and 202 variables:
- bwgaz
Outcome to be used. Simulated birth weight for gestational age z-score.
- ChildSex
Binary sex of child.
- MomAge
Continuous age in years.
- GestAge
Continuous estimated gestational age at birth in weeks.
- MomHeightIn
Continuous maternal height in inches.
- MomPriorWeightLbs
Continuous mothers pre-pregnancy weight in pounds.
- MomPriorBMI
Continuous mothers pre-pregnancy BMI.
- race
Categorical race.
- Hispanic
Binary indicator of Hispanic.
- MomEdu
Categorical maternal heighest educational attainment.
- SmkAny
Binary indicator of any smoking during pregnancy.
- Marital
Categorical maternal marital status.
- Income
Categorical income.
- EstDateConcept
Estimated date of conception.
- EstMonthConcept
Estimated month of conception.
- EstYearConcept
Estimated year of conception.
- pm25_1
Exposure to be used. Weekly average exposure to PM2.5 in week 1 of gestation.
- pm25_2
Exposure to be used. Weekly average exposure to PM2.5 in week 2 of gestation.
- pm25_3
Exposure to be used. Weekly average exposure to PM2.5 in week 3 of gestation.
- pm25_4
Exposure to be used. Weekly average exposure to PM2.5 in week 4 of gestation.
- pm25_5
Exposure to be used. Weekly average exposure to PM2.5 in week 5 of gestation.
- pm25_6
Exposure to be used. Weekly average exposure to PM2.5 in week 6 of gestation.
- pm25_7
Exposure to be used. Weekly average exposure to PM2.5 in week 7 of gestation.
- pm25_8
Exposure to be used. Weekly average exposure to PM2.5 in week 8 of gestation.
- pm25_9
Exposure to be used. Weekly average exposure to PM2.5 in week 9 of gestation.
- pm25_10
Exposure to be used. Weekly average exposure to PM2.5 in week 10 of gestation.
- pm25_11
Exposure to be used. Weekly average exposure to PM2.5 in week 11 of gestation.
- pm25_12
Exposure to be used. Weekly average exposure to PM2.5 in week 12 of gestation.
- pm25_13
Exposure to be used. Weekly average exposure to PM2.5 in week 13 of gestation.
- pm25_14
Exposure to be used. Weekly average exposure to PM2.5 in week 14 of gestation.
- pm25_15
Exposure to be used. Weekly average exposure to PM2.5 in week 15 of gestation.
- pm25_16
Exposure to be used. Weekly average exposure to PM2.5 in week 16 of gestation.
- pm25_17
Exposure to be used. Weekly average exposure to PM2.5 in week 17 of gestation.
- pm25_18
Exposure to be used. Weekly average exposure to PM2.5 in week 18 of gestation.
- pm25_19
Exposure to be used. Weekly average exposure to PM2.5 in week 19 of gestation.
- pm25_20
Exposure to be used. Weekly average exposure to PM2.5 in week 20 of gestation.
- pm25_21
Exposure to be used. Weekly average exposure to PM2.5 in week 21 of gestation.
- pm25_22
Exposure to be used. Weekly average exposure to PM2.5 in week 22 of gestation.
- pm25_23
Exposure to be used. Weekly average exposure to PM2.5 in week 23 of gestation.
- pm25_24
Exposure to be used. Weekly average exposure to PM2.5 in week 24 of gestation.
- pm25_25
Exposure to be used. Weekly average exposure to PM2.5 in week 25 of gestation.
- pm25_26
Exposure to be used. Weekly average exposure to PM2.5 in week 26 of gestation.
- pm25_27
Exposure to be used. Weekly average exposure to PM2.5 in week 27 of gestation.
- pm25_28
Exposure to be used. Weekly average exposure to PM2.5 in week 28 of gestation.
- pm25_29
Exposure to be used. Weekly average exposure to PM2.5 in week 29 of gestation.
- pm25_30
Exposure to be used. Weekly average exposure to PM2.5 in week 30 of gestation.
- pm25_31
Exposure to be used. Weekly average exposure to PM2.5 in week 31 of gestation.
- pm25_32
Exposure to be used. Weekly average exposure to PM2.5 in week 32 of gestation.
- pm25_33
Exposure to be used. Weekly average exposure to PM2.5 in week 33 of gestation.
- pm25_34
Exposure to be used. Weekly average exposure to PM2.5 in week 34 of gestation.
- pm25_35
Exposure to be used. Weekly average exposure to PM2.5 in week 35 of gestation.
- pm25_36
Exposure to be used. Weekly average exposure to PM2.5 in week 36 of gestation.
- pm25_37
Exposure to be used. Weekly average exposure to PM2.5 in week 37 of gestation.
- no2_1
Exposure to be used. Weekly average exposure to NO2 in week 1 of gestation.
- no2_2
Exposure to be used. Weekly average exposure to NO2 in week 2 of gestation.
- no2_3
Exposure to be used. Weekly average exposure to NO2 in week 3 of gestation.
- no2_4
Exposure to be used. Weekly average exposure to NO2 in week 4 of gestation.
- no2_5
Exposure to be used. Weekly average exposure to NO2 in week 5 of gestation.
- no2_6
Exposure to be used. Weekly average exposure to NO2 in week 6 of gestation.
- no2_7
Exposure to be used. Weekly average exposure to NO2 in week 7 of gestation.
- no2_8
Exposure to be used. Weekly average exposure to NO2 in week 8 of gestation.
- no2_9
Exposure to be used. Weekly average exposure to NO2 in week 9 of gestation.
- no2_10
Exposure to be used. Weekly average exposure to NO2 in week 10 of gestation.
- no2_11
Exposure to be used. Weekly average exposure to NO2 in week 11 of gestation.
- no2_12
Exposure to be used. Weekly average exposure to NO2 in week 12 of gestation.
- no2_13
Exposure to be used. Weekly average exposure to NO2 in week 13 of gestation.
- no2_14
Exposure to be used. Weekly average exposure to NO2 in week 14 of gestation.
- no2_15
Exposure to be used. Weekly average exposure to NO2 in week 15 of gestation.
- no2_16
Exposure to be used. Weekly average exposure to NO2 in week 16 of gestation.
- no2_17
Exposure to be used. Weekly average exposure to NO2 in week 17 of gestation.
- no2_18
Exposure to be used. Weekly average exposure to NO2 in week 18 of gestation.
- no2_19
Exposure to be used. Weekly average exposure to NO2 in week 19 of gestation.
- no2_20
Exposure to be used. Weekly average exposure to NO2 in week 20 of gestation.
- no2_21
Exposure to be used. Weekly average exposure to NO2 in week 21 of gestation.
- no2_22
Exposure to be used. Weekly average exposure to NO2 in week 22 of gestation.
- no2_23
Exposure to be used. Weekly average exposure to NO2 in week 23 of gestation.
- no2_24
Exposure to be used. Weekly average exposure to NO2 in week 24 of gestation.
- no2_25
Exposure to be used. Weekly average exposure to NO2 in week 25 of gestation.
- no2_26
Exposure to be used. Weekly average exposure to NO2 in week 26 of gestation.
- no2_27
Exposure to be used. Weekly average exposure to NO2 in week 27 of gestation.
- no2_28
Exposure to be used. Weekly average exposure to NO2 in week 28 of gestation.
- no2_29
Exposure to be used. Weekly average exposure to NO2 in week 29 of gestation.
- no2_30
Exposure to be used. Weekly average exposure to NO2 in week 30 of gestation.
- no2_31
Exposure to be used. Weekly average exposure to NO2 in week 31 of gestation.
- no2_32
Exposure to be used. Weekly average exposure to NO2 in week 32 of gestation.
- no2_33
Exposure to be used. Weekly average exposure to NO2 in week 33 of gestation.
- no2_34
Exposure to be used. Weekly average exposure to NO2 in week 34 of gestation.
- no2_35
Exposure to be used. Weekly average exposure to NO2 in week 35 of gestation.
- no2_36
Exposure to be used. Weekly average exposure to NO2 in week 36 of gestation.
- no2_37
Exposure to be used. Weekly average exposure to NO2 in week 37 of gestation.
- so2_1
Exposure to be used. Weekly average exposure to SO2 in week 1 of gestation.
- so2_2
Exposure to be used. Weekly average exposure to SO2 in week 2 of gestation.
- so2_3
Exposure to be used. Weekly average exposure to SO2 in week 3 of gestation.
- so2_4
Exposure to be used. Weekly average exposure to SO2 in week 4 of gestation.
- so2_5
Exposure to be used. Weekly average exposure to SO2 in week 5 of gestation.
- so2_6
Exposure to be used. Weekly average exposure to SO2 in week 6 of gestation.
- so2_7
Exposure to be used. Weekly average exposure to SO2 in week 7 of gestation.
- so2_8
Exposure to be used. Weekly average exposure to SO2 in week 8 of gestation.
- so2_9
Exposure to be used. Weekly average exposure to SO2 in week 9 of gestation.
- so2_10
Exposure to be used. Weekly average exposure to SO2 in week 10 of gestation.
- so2_11
Exposure to be used. Weekly average exposure to SO2 in week 11 of gestation.
- so2_12
Exposure to be used. Weekly average exposure to SO2 in week 12 of gestation.
- so2_13
Exposure to be used. Weekly average exposure to SO2 in week 13 of gestation.
- so2_14
Exposure to be used. Weekly average exposure to SO2 in week 14 of gestation.
- so2_15
Exposure to be used. Weekly average exposure to SO2 in week 15 of gestation.
- so2_16
Exposure to be used. Weekly average exposure to SO2 in week 16 of gestation.
- so2_17
Exposure to be used. Weekly average exposure to SO2 in week 17 of gestation.
- so2_18
Exposure to be used. Weekly average exposure to SO2 in week 18 of gestation.
- so2_19
Exposure to be used. Weekly average exposure to SO2 in week 19 of gestation.
- so2_20
Exposure to be used. Weekly average exposure to SO2 in week 20 of gestation.
- so2_21
Exposure to be used. Weekly average exposure to SO2 in week 21 of gestation.
- so2_22
Exposure to be used. Weekly average exposure to SO2 in week 22 of gestation.
- so2_23
Exposure to be used. Weekly average exposure to SO2 in week 23 of gestation.
- so2_24
Exposure to be used. Weekly average exposure to SO2 in week 24 of gestation.
- so2_25
Exposure to be used. Weekly average exposure to SO2 in week 25 of gestation.
- so2_26
Exposure to be used. Weekly average exposure to SO2 in week 26 of gestation.
- so2_27
Exposure to be used. Weekly average exposure to SO2 in week 27 of gestation.
- so2_28
Exposure to be used. Weekly average exposure to SO2 in week 28 of gestation.
- so2_29
Exposure to be used. Weekly average exposure to SO2 in week 29 of gestation.
- so2_30
Exposure to be used. Weekly average exposure to SO2 in week 30 of gestation.
- so2_31
Exposure to be used. Weekly average exposure to SO2 in week 31 of gestation.
- so2_32
Exposure to be used. Weekly average exposure to SO2 in week 32 of gestation.
- so2_33
Exposure to be used. Weekly average exposure to SO2 in week 33 of gestation.
- so2_34
Exposure to be used. Weekly average exposure to SO2 in week 34 of gestation.
- so2_35
Exposure to be used. Weekly average exposure to SO2 in week 35 of gestation.
- so2_36
Exposure to be used. Weekly average exposure to SO2 in week 36 of gestation.
- so2_37
Exposure to be used. Weekly average exposure to SO2 in week 37 of gestation.
- co_1
Exposure to be used. Weekly average exposure to CO in week 1 of gestation.
- co_2
Exposure to be used. Weekly average exposure to CO in week 2 of gestation.
- co_3
Exposure to be used. Weekly average exposure to CO in week 3 of gestation.
- co_4
Exposure to be used. Weekly average exposure to CO in week 4 of gestation.
- co_5
Exposure to be used. Weekly average exposure to CO in week 5 of gestation.
- co_6
Exposure to be used. Weekly average exposure to CO in week 6 of gestation.
- co_7
Exposure to be used. Weekly average exposure to CO in week 7 of gestation.
- co_8
Exposure to be used. Weekly average exposure to CO in week 8 of gestation.
- co_9
Exposure to be used. Weekly average exposure to CO in week 9 of gestation.
- co_10
Exposure to be used. Weekly average exposure to CO in week 10 of gestation.
- co_11
Exposure to be used. Weekly average exposure to CO in week 11 of gestation.
- co_12
Exposure to be used. Weekly average exposure to CO in week 12 of gestation.
- co_13
Exposure to be used. Weekly average exposure to CO in week 13 of gestation.
- co_14
Exposure to be used. Weekly average exposure to CO in week 14 of gestation.
- co_15
Exposure to be used. Weekly average exposure to CO in week 15 of gestation.
- co_16
Exposure to be used. Weekly average exposure to CO in week 16 of gestation.
- co_17
Exposure to be used. Weekly average exposure to CO in week 17 of gestation.
- co_18
Exposure to be used. Weekly average exposure to CO in week 18 of gestation.
- co_19
Exposure to be used. Weekly average exposure to CO in week 19 of gestation.
- co_20
Exposure to be used. Weekly average exposure to CO in week 20 of gestation.
- co_21
Exposure to be used. Weekly average exposure to CO in week 21 of gestation.
- co_22
Exposure to be used. Weekly average exposure to CO in week 22 of gestation.
- co_23
Exposure to be used. Weekly average exposure to CO in week 23 of gestation.
- co_24
Exposure to be used. Weekly average exposure to CO in week 24 of gestation.
- co_25
Exposure to be used. Weekly average exposure to CO in week 25 of gestation.
- co_26
Exposure to be used. Weekly average exposure to CO in week 26 of gestation.
- co_27
Exposure to be used. Weekly average exposure to CO in week 27 of gestation.
- co_28
Exposure to be used. Weekly average exposure to CO in week 28 of gestation.
- co_29
Exposure to be used. Weekly average exposure to CO in week 29 of gestation.
- co_30
Exposure to be used. Weekly average exposure to CO in week 30 of gestation.
- co_31
Exposure to be used. Weekly average exposure to CO in week 31 of gestation.
- co_32
Exposure to be used. Weekly average exposure to CO in week 32 of gestation.
- co_33
Exposure to be used. Weekly average exposure to CO in week 33 of gestation.
- co_34
Exposure to be used. Weekly average exposure to CO in week 34 of gestation.
- co_35
Exposure to be used. Weekly average exposure to CO in week 35 of gestation.
- co_36
Exposure to be used. Weekly average exposure to CO in week 36 of gestation.
- co_37
Exposure to be used. Weekly average exposure to CO in week 37 of gestation.
- temp_1
Exposure to be used. Weekly average exposure to temperature in week 1 of gestation.
- temp_2
Exposure to be used. Weekly average exposure to temperature in week 2 of gestation.
- temp_3
Exposure to be used. Weekly average exposure to temperature in week 3 of gestation.
- temp_4
Exposure to be used. Weekly average exposure to temperature in week 4 of gestation.
- temp_5
Exposure to be used. Weekly average exposure to temperature in week 5 of gestation.
- temp_6
Exposure to be used. Weekly average exposure to temperature in week 6 of gestation.
- temp_7
Exposure to be used. Weekly average exposure to temperature in week 7 of gestation.
- temp_8
Exposure to be used. Weekly average exposure to temperature in week 8 of gestation.
- temp_9
Exposure to be used. Weekly average exposure to temperature in week 9 of gestation.
- temp_10
Exposure to be used. Weekly average exposure to temperature in week 10 of gestation.
- temp_11
Exposure to be used. Weekly average exposure to temperature in week 11 of gestation.
- temp_12
Exposure to be used. Weekly average exposure to temperature in week 12 of gestation.
- temp_13
Exposure to be used. Weekly average exposure to temperature in week 13 of gestation.
- temp_14
Exposure to be used. Weekly average exposure to temperature in week 14 of gestation.
- temp_15
Exposure to be used. Weekly average exposure to temperature in week 15 of gestation.
- temp_16
Exposure to be used. Weekly average exposure to temperature in week 16 of gestation.
- temp_17
Exposure to be used. Weekly average exposure to temperature in week 17 of gestation.
- temp_18
Exposure to be used. Weekly average exposure to temperature in week 18 of gestation.
- temp_19
Exposure to be used. Weekly average exposure to temperature in week 19 of gestation.
- temp_20
Exposure to be used. Weekly average exposure to temperature in week 20 of gestation.
- temp_21
Exposure to be used. Weekly average exposure to temperature in week 21 of gestation.
- temp_22
Exposure to be used. Weekly average exposure to temperature in week 22 of gestation.
- temp_23
Exposure to be used. Weekly average exposure to temperature in week 23 of gestation.
- temp_24
Exposure to be used. Weekly average exposure to temperature in week 24 of gestation.
- temp_25
Exposure to be used. Weekly average exposure to temperature in week 25 of gestation.
- temp_26
Exposure to be used. Weekly average exposure to temperature in week 26 of gestation.
- temp_27
Exposure to be used. Weekly average exposure to temperature in week 27 of gestation.
- temp_28
Exposure to be used. Weekly average exposure to temperature in week 28 of gestation.
- temp_29
Exposure to be used. Weekly average exposure to temperature in week 29 of gestation.
- temp_30
Exposure to be used. Weekly average exposure to temperature in week 30 of gestation.
- temp_31
Exposure to be used. Weekly average exposure to temperature in week 31 of gestation.
- temp_32
Exposure to be used. Weekly average exposure to temperature in week 32 of gestation.
- temp_33
Exposure to be used. Weekly average exposure to temperature in week 33 of gestation.
- temp_34
Exposure to be used. Weekly average exposure to temperature in week 34 of gestation.
- temp_35
Exposure to be used. Weekly average exposure to temperature in week 35 of gestation.
- temp_36
Exposure to be used. Weekly average exposure to temperature in week 36 of gestation.
- temp_37
Exposure to be used. Weekly average exposure to temperature in week 37 of gestation.
- source
Variable indicating that the data came from the bdlim package.
Summary for bdlim1
Description
Summary for bdlim1
Usage
## S3 method for class 'bdlim1'
summary(object, ...)
Arguments
object |
An object of class bdlim1. |
... |
Not used. |
Value
An object of class summary.bdlim1.
Summary for bdlim4
Description
Summary for bdlim4
Usage
## S3 method for class 'bdlim4'
summary(object, model = NULL, ...)
Arguments
object |
An object of class bdlim4. |
model |
Pattern of heterogeneity to be printed. If not specified (default) the best fitting model will be used. Options are "n", "b", "w" and "bw" where b indicates the effect sizes are subgroup specific and w indicates the weight functions are subgroups specific. |
... |
Other arguments |
Value
An object of class summary.bdlim4.
Examples
# run BDLIM with modification by ChildSex
fit_sex <- bdlim4(
y = sbd_bdlim$bwgaz,
exposure = sbd_bdlim[,paste0("pm25_",1:37)],
covars = sbd_bdlim[,c("MomPriorBMI","MomAge","race","Hispanic",
"EstMonthConcept","EstYearConcept")],
group = as.factor(sbd_bdlim$ChildSex),
df = 5,
nits = 5000,
parallel = FALSE
)
#summarize results
summary(fit_sex)
# obtain estimates of the distributed lag function
# these are note displayed when printed but available for use
sfit_sex <- summary(fit_sex)
head(sfit_sex$dlfun)
# can summarize with a specific model
sfit_hisp_n <- summary(fit_sex, model="n") # no modification
sfit_hisp_b <- summary(fit_sex, model="b") # subgroup-specific effects (beta)
sfit_hisp_w <- summary(fit_sex, model="w") # subgroup-specific weight function
sfit_hisp_bw <- summary(fit_sex, model="bw") # both subgroup-specific