rhc_X: Right Heart Catheterization Data
In optrefine: Optimally Refine Strata
rhc_X R Documentation
Right Heart Catheterization Data
Description
The data in the example are from Frank Harrell's Hmisc package.
The data there are very similar to the
data in Connors et al. (1996), but do not exactly reproduce analyses from
that article. So, we employ the version of that analysis in the
documentation for Ruoqi Yu's RBestMatch package,
which attempts to be close to the analysis in Connors et al.
In Yu's version, the propensity score (her
pr) is built using 76 covariates, and the focus of attention is on
26 "priority" covariates (her X) and the propensity score
that were emphasized in the Connors et al. article, including those in that
article's Table 3.
Usage
rhc_X
Format
Matrix with 5,735 rows and 28 columns:
- aps1
APACHE score
- surv2md1
Support model estimate of the prob. of surviving 2 months
- age
Age
- NumComorbid
Number of comorbidities
- adld3p_impute
ADL with missing data imputed
- adld3p_na
ADL missing
- das2d3pc
DASI (Duke Activity Status Index)
- temp1
Temperature
- hrt1
Heart rate
- meanbp1
Mean blood pressure
- resp1
Respiratory rate
- wblc1
WBC
- pafi1
PaO2/FIO2 ratio
- paco21
PaCo2
- ph1
PH
- crea1
Creatinine
- alb1
Albumin
- scoma1
Glasgow Coma Score
- cat1_copd
Primary disease category COPD
- cat1_mosfsep
Primary disease category MOSF w sepsis
- cat1_mosfmal
Primary disease category MOSF w malignancy
- cat1_chf
Primary disease category CHF
- cat1_coma
Primary disease category coma
- cat1_cirr
Primary disease category cirrhosis
- cat1_lung
Primary disease category lung cancer
- cat1_colon
Primary disease category colon cancer
- pr
Propensity score using 76 covariates
- z
Treatment indicator
References
Connors et al. (1996): The effectiveness of RHC in the initial
care of critically ill patients. J American Medical Association 276:889-897.
optrefine documentation built on April 19, 2023, 1:08 a.m.
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| rhc_X | R Documentation |
Right Heart Catheterization Data
Description
The data in the example are from Frank Harrell's Hmisc package.
The data there are very similar to the
data in Connors et al. (1996), but do not exactly reproduce analyses from
that article. So, we employ the version of that analysis in the
documentation for Ruoqi Yu's RBestMatch package,
which attempts to be close to the analysis in Connors et al.
In Yu's version, the propensity score (her
pr) is built using 76 covariates, and the focus of attention is on
26 "priority" covariates (her X) and the propensity score
that were emphasized in the Connors et al. article, including those in that
article's Table 3.
Usage
rhc_X
Format
Matrix with 5,735 rows and 28 columns:
- aps1
APACHE score
- surv2md1
Support model estimate of the prob. of surviving 2 months
- age
Age
- NumComorbid
Number of comorbidities
- adld3p_impute
ADL with missing data imputed
- adld3p_na
ADL missing
- das2d3pc
DASI (Duke Activity Status Index)
- temp1
Temperature
- hrt1
Heart rate
- meanbp1
Mean blood pressure
- resp1
Respiratory rate
- wblc1
WBC
- pafi1
PaO2/FIO2 ratio
- paco21
PaCo2
- ph1
PH
- crea1
Creatinine
- alb1
Albumin
- scoma1
Glasgow Coma Score
- cat1_copd
Primary disease category COPD
- cat1_mosfsep
Primary disease category MOSF w sepsis
- cat1_mosfmal
Primary disease category MOSF w malignancy
- cat1_chf
Primary disease category CHF
- cat1_coma
Primary disease category coma
- cat1_cirr
Primary disease category cirrhosis
- cat1_lung
Primary disease category lung cancer
- cat1_colon
Primary disease category colon cancer
- pr
Propensity score using 76 covariates
- z
Treatment indicator
References
Connors et al. (1996): The effectiveness of RHC in the initial care of critically ill patients. J American Medical Association 276:889-897.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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