| Type: | Package |
| Title: | Integrate Single-Arm Observational Data in Network Meta Analysis |
| Version: | 0.1.0 |
| Date: | 2024-08-07 |
| Maintainer: | Shubhram Pandey <shubhram1992@gmail.com> |
| Description: | Calculate the distance between single-arm observational studies using covariate information to remove heterogeneity in Network Meta-Analysis (NMA) of randomized clinical trials. Facilitate the inclusion of observational data in NMA, enhancing the comprehensiveness and robustness of comparative effectiveness research. Schmitz (2018) <doi:10.1186/s12874-018-0509-7>. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| Imports: | combinat |
| RoxygenNote: | 7.3.1 |
| Depends: | R (≥ 3.5.0) |
| Suggests: | knitr, rmarkdown |
| VignetteBuilder: | knitr |
| URL: | https://github.com/heorlytics/closeloop |
| NeedsCompilation: | no |
| Packaged: | 2024-07-12 12:00:18 UTC; ShubhramPandey |
| Author: | Supreet Kaur [ctb], Akanksha Sharma [ctb], Shubhram Pandey [aut, cre] |
| Repository: | CRAN |
| Date/Publication: | 2024-07-14 12:00:09 UTC |
Title To calculate distance between two studies using covariate information
Description
Title To calculate distance between two studies using covariate information
Usage
calc_dist(df, col_names, Study = "Study", Treat = "Treatment", weights, digits)
Arguments
df |
A data frame consists of columns namely "Study", "Treatment", and at least one covariate. |
col_names |
A vector of column names specifying covariate names. |
Study |
A column name in a data frame named as "Study" specifying study names. |
Treat |
A column name in a data frame named as "Treatment" specifying treatment names. |
weights |
A variable in which the results of specify_weight() function was stored. |
digits |
A numeric value indicating the number of decimal places in the Distance calculated. |
Value
Data frame
Author(s)
Shubhram Pandey shubhram1992@gmail.com
Examples
attach(exampleData)
var = c("Male","Age")
weights = specify_weight(var, weights = c(0.5,0.5))
weights
dist = calc_dist(df = exampleData, col_names = var, weights = weights,digits = 4)
dist
Function to check if all values are numeric in data
Description
Function to check if all values are numeric in data
Usage
check_data(df, col_names = NULL)
Arguments
df |
A data frame contains columns that represent covariates |
col_names |
A numeric vector of covariates that can be binary or continuous |
Value
logical
Author(s)
Shubhram Pandey shubhram1992@gmail.com
Examples
attach(exampleData)
var = c("Age","Male")
x = check_data(df = exampleData, col_names = var)
x
This is a simulated data
Description
Data were extracted from the studies included.
Usage
exampleData
Format
A data frame with with the 4 following variables (columns).
- Study
This character vector represents number of the study.
- Male
This vector represents the proportion of males.
- Age
This vector represents the average age in each study.
- Treatment
This vector represents the treatment.
...
Details
A simulated data were created to run examples.
Author(s)
Shubhram Pandey shubhram.pandey@heorlytics.com
Function to check if columns are proportions
Description
Function to check if columns are proportions
Usage
is_prop(df, col_names)
Arguments
df |
a data frame to be checked |
col_names |
column names to be checked |
Value
list
Author(s)
Shubhram Pandey shubhram1992@gmail.com
Examples
#' attach(exampleData)
result <- is_prop(exampleData,c("Male","Age"))
result
Title specify_weight
Description
Title specify_weight
Usage
specify_weight(var, weights)
Arguments
var |
Variables for which weights can be assigned |
weights |
weights in same sequence as variables |
Value
list
Author(s)
Shubhram Pandey shubhram1992@gmail.com
Examples
var = c("Male","Age")
weights = specify_weight(var, weights = c(0.5,0.5))
weights