stpm: an R package for stochastic process model

BMC Bioinformatics

Table 1 Example of longitudinal dataset

ID^a	IndicatorDeath^b	Age	AgeNext	DBP^c	BMI
1	0	30	32	80	25.00
1	0	32	34	80	26.61
1	1	34	35.34	NA	NA
2	0	30	38	77	32.40
2	0	38	40	94	31.92
2	0	40	40.56	88	32.89
...	...	...	...	...	...
2	0	80	80.55	83	26.71
...

^aA subject identification number
^b IndicatorDeath shows that death occurred (IndicatorDeath=1) or did not occur (IndicatorDeath=0) between Age and AgeNext. Age for the next observation of the same individual must coincide with AgeNext of the current observation. AgeNext is a censoring age for the last observation.
^c DBP and BMI are measured at age Age and are diastolic blood pressure and body mass index. They are covariates. If some values of covariates are missing (but the subject is alive), they are imputed during the data preparation stage (see section “Data preparation”)

ISSN: 1471-2105