Paq810: Filtered Paquid Sample Data Set for Illness-Death Modeling
In frailtypack: Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints
Paq810 R Documentation
Filtered Paquid Sample Data Set for Illness-Death Modeling
Description
A dataset derived from Paq1000 (originally a sample from the Paquid
study available via the SmoothHazard package). This version excludes
subjects where the age of dementia diagnosis or censoring ('r') was exactly
equal to the age at study entry ('e'), ensuring valid observation intervals
when using left truncation.
Usage
data(Paq810)
Format
A data frame with approximately 810 rows (original 1000 minus exclusions)
and the following 8 columns:
- dementia
Dementia status indicator: 0 = non-demented, 1 = demented.
- death
Death status indicator: 0 = alive, 1 = dead.
- e
Age at entry into the study (left-truncation time).
- l
For demented subjects: age at the visit *before* the diagnostic visit. For non-demented subjects: age at the last visit.
- r
Age at dementia diagnosis or censoring for dementia (event/censoring time for 0->1 transition). Guaranteed to be > 'e'.
- t
Overall exit age. For dead subjects: age at death. For alive subjects: age at the latest news (censoring time for death).
- certif
Primary school certificate indicator: 0 = without certificate, 1 = with certificate.
- gender
Gender indicator: 0 = female, 1 = male.
Details
This dataset was created by filtering the Paq1000 data:
Paq810 <- Paq1000[Paq1000$r > Paq1000$e, ].
This step is necessary to prevent issues with survival::Surv(e, r, dementia)
which requires the stop time ('r') to be strictly greater than the start/entry
time ('e').
The time variables 'e', 'l', 'r', and 't' are all ages in years.
This dataset is suitable for fitting illness-death models with left truncation
using functions like IllnessDeath.
Source
Derived from the Paq1000 dataset, which originates from the
Paquid study and is included in the SmoothHazard package.
See Also
Paq1000, The SmoothHazard package.
frailtypack documentation built on Nov. 23, 2025, 1:09 a.m.
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| Paq810 | R Documentation |
Filtered Paquid Sample Data Set for Illness-Death Modeling
Description
A dataset derived from Paq1000 (originally a sample from the Paquid
study available via the SmoothHazard package). This version excludes
subjects where the age of dementia diagnosis or censoring ('r') was exactly
equal to the age at study entry ('e'), ensuring valid observation intervals
when using left truncation.
Usage
data(Paq810)
Format
A data frame with approximately 810 rows (original 1000 minus exclusions) and the following 8 columns:
- dementia
Dementia status indicator: 0 = non-demented, 1 = demented.
- death
Death status indicator: 0 = alive, 1 = dead.
- e
Age at entry into the study (left-truncation time).
- l
For demented subjects: age at the visit *before* the diagnostic visit. For non-demented subjects: age at the last visit.
- r
Age at dementia diagnosis or censoring for dementia (event/censoring time for 0->1 transition). Guaranteed to be > 'e'.
- t
Overall exit age. For dead subjects: age at death. For alive subjects: age at the latest news (censoring time for death).
- certif
Primary school certificate indicator: 0 = without certificate, 1 = with certificate.
- gender
Gender indicator: 0 = female, 1 = male.
Details
This dataset was created by filtering the Paq1000 data:
Paq810 <- Paq1000[Paq1000$r > Paq1000$e, ].
This step is necessary to prevent issues with survival::Surv(e, r, dementia)
which requires the stop time ('r') to be strictly greater than the start/entry
time ('e').
The time variables 'e', 'l', 'r', and 't' are all ages in years.
This dataset is suitable for fitting illness-death models with left truncation
using functions like IllnessDeath.
Source
Derived from the Paq1000 dataset, which originates from the
Paquid study and is included in the SmoothHazard package.
See Also
Paq1000, The SmoothHazard package.
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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