The name is absent



46


Step 4, => Keep updating βim+1'> and ^m+1^ until they converge respectively

Step 5, ≠> Let m = m + l, repeat steps 2, 3 and 4 until β(m+1'> and β^l+1^i converge
respectively.

Consequently, we could get estimated hazard functions Λ(∙) and Ψ(∙), and survival
functions S(∙) and R(β.

Specifically, at Step 1,

Assuming independent censoring, we fit two Cox proportional hazards models to
get initial estimators β^ and βc°'1 for β and βc, respectively. Then we use the Breslow
(1972) method to obtain estimators for baseline cumulative hazard functions, which
give estimates of baseline survival functions.

• Baseline survival functions

For an event T and i < k, we have

^obsii1            -)

£ exp(Z'kβ^γ'
obsh>obsi


(3.13)


S,o°∖θ = eτp{-A^(t)} = exp{-

obsi<t

For dependent censoring C and i < k, we have

7⅜⅜) =


exp{-Φ^(t)} = exp{-

obsi<t


^obsi,2          ɪ

£ exp(Wkβ^γ,
obδk'>obsi


(3.14)


• Marginal cumulative distribution functions



More intriguing information

1. A Rare Presentation of Crohn's Disease
2. Wirkung einer Feiertagsbereinigung des Länderfinanzausgleichs: eine empirische Analyse des deutschen Finanzausgleichs
3. THE RISE OF RURAL-TO-RURAL LABOR MARKETS IN CHINA
4. L'organisation en réseau comme forme « indéterminée »
5. Luce Irigaray and divine matter
6. The Shepherd Sinfonia
7. Conditions for learning: partnerships for engaging secondary pupils with contemporary art.
8. Bird’s Eye View to Indonesian Mass Conflict Revisiting the Fact of Self-Organized Criticality
9. The name is absent
10. Chebyshev polynomial approximation to approximate partial differential equations