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| Original file line number | Diff line number | Diff line change |
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| """ | ||
| Remove the last element from an LSurvivalResp object | ||
| ```julia | ||
| id, int, outt, data = | ||
| LSurvival.dgm(MersenneTwister(112), 100, 10; afun = LSurvival.int_0) | ||
| data[:, 1] = round.(data[:, 1], digits = 3) | ||
| d, X = data[:, 4], data[:, 1:3] | ||
| wt = rand(length(d)) | ||
| wt ./= (sum(wt) / length(wt)) | ||
| R = LSurvivalResp(int, outt, d, ID.(id)) # specification with ID only | ||
| Ri, Rj, idxi, idxj = pop(R); | ||
| ``` | ||
| """ | ||
| function pop(R::T) where {T<:LSurvivalResp} | ||
| uid = unique(R.id)[end] | ||
| idx = findall(getfield.(R.id, :value) .== uid.value) | ||
| nidx = setdiff(collect(eachindex(R.id)),idx) | ||
| Ri = LSurvivalResp(R.enter[idx], R.exit[idx], R.y[idx], R.wts[idx], R.id[idx]; origintime= R.origin) | ||
| Rj = LSurvivalResp(R.enter[nidx], R.exit[nidx], R.y[nidx], R.wts[nidx], R.id[nidx],origintime= R.origin) | ||
| Ri, Rj, idx, nidx | ||
| end | ||
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||
| """ | ||
| id, int, outt, data = | ||
| LSurvival.dgm(MersenneTwister(112), 100, 10; afun = LSurvival.int_0) | ||
| data[:, 1] = round.(data[:, 1], digits = 3) | ||
| d, X = data[:, 4], data[:, 1:3] | ||
| wt = rand(length(d)) | ||
| wt ./= (sum(wt) / length(wt)) | ||
| P = PHParms(X) | ||
| R = LSurvivalResp(int, outt, d, ID.(id)) # specification with ID only | ||
| Ri, Rj, idxi, idxj = pop(R); | ||
| Pi = popat!(P, idxi, idxj) | ||
| """ | ||
| function popat!(P::T, idxi, idxj) where {T<:PHParms} | ||
| Pi = PHParms(P.X[idxi,:], P._B, P._r[idxi], P._LL, P._grad, P._hess, 1, P.p) | ||
| P.X = P.X[idxj,:] | ||
| P._r = P._r[idxj] | ||
| P.n -= length(idxi) | ||
| Pi | ||
| end | ||
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| """ | ||
| Insert an observation into the front of an LSurvivalResp object | ||
| ```julia | ||
| id, int, outt, data = | ||
| LSurvival.dgm(MersenneTwister(112), 100, 10; afun = LSurvival.int_0) | ||
| data[:, 1] = round.(data[:, 1], digits = 3) | ||
| d, X = data[:, 4], data[:, 1:3] | ||
| wt = rand(length(d)) | ||
| wt ./= (sum(wt) / length(wt)) | ||
| R = LSurvivalResp(int, outt, d, ID.(id)) # specification with ID only | ||
| Ri, Rj, idxi, idxj = pop(R); | ||
| R = push(Ri, Rj) | ||
| ``` | ||
| """ | ||
| function push(Ri::T, Rj::T) where {T<:LSurvivalResp} | ||
| Ri = LSurvivalResp( | ||
| vcat(Ri.enter, Rj.enter), | ||
| vcat(Ri.exit, Rj.exit), | ||
| vcat(Ri.y, Rj.y), | ||
| vcat(Ri.wts, Rj.wts), | ||
| vcat(Ri.id, Rj.id); | ||
| origintime= min(Ri.origin, Rj.origin)) | ||
| end | ||
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| """ | ||
| Insert an observation into the front of an PHParms object | ||
| """ | ||
| function push!(Pi::T, Pj::T) where {T<:PHParms} | ||
| Pj.X = vcat(Pi.X, Pj.X) | ||
| Pj._r = vcat(Pi._r, Pj._r) | ||
| Pj.n +=1 | ||
| nothing | ||
| end | ||
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| """ | ||
| id, int, outt, data = | ||
| LSurvival.dgm(MersenneTwister(112), 100, 10; afun = LSurvival.int_0) | ||
| data[:, 1] = round.(data[:, 1], digits = 3) | ||
| d, X = data[:, 4], data[:, 1:3] | ||
| wt = rand(length(d)) | ||
| wt ./= (sum(wt) / length(wt)) | ||
| m = coxph(X,int, outt,d, wts=wt, id=ID.(id)) | ||
| jk = jackknife(m); | ||
| bs = bootstrap(MersenneTwister(12321), m, 1000); | ||
| N = nobs(m) | ||
| #comparing estimate with jackknife estimate with bootstrap mean | ||
| hcat(coef(m), mean(jk, dims=1)[1,:], mean(bs, dims=1)[1,:]) | ||
| semb = stderror(m) | ||
| sebs = std(bs, dims=1) | ||
| sejk = std(jk, dims=1, corrected=false) .* sqrt(N-1) | ||
| sero = stderror(m, type="robust") | ||
| jackknife_vcov(m) | ||
| LSurvival.robust_vcov(m) | ||
| hcat(semb, sebs[1,:], sejk[1,:], sero) | ||
| dat1 = (time = [1, 1, 6, 6, 8, 9], status = [1, 0, 1, 1, 0, 1], x = [1, 1, 1, 0, 0, 0]) | ||
| dat1clust = ( | ||
| id = [1, 2, 3, 3, 4, 4, 5, 5, 6, 6], | ||
| enter = [0, 0, 0, 1, 0, 1, 0, 1, 0, 1], | ||
| exit = [1, 1, 1, 6, 1, 6, 1, 8, 1, 9], | ||
| status = [1, 0, 0, 1, 0, 1, 0, 0, 0, 1], | ||
| x = [1, 1, 1, 1, 0, 0, 0, 0, 0, 0], | ||
| ) | ||
| m = coxph(@formula(Surv(time, status)~x),dat1) | ||
| mc = coxph(@formula(Surv(enter, exit, status)~x),dat1clust, id=ID.(dat1clust.id)) | ||
| jk = jackknife(m); | ||
| jkc = jackknife(mc); | ||
| bs = bootstrap(mc, 100); | ||
| std(bs[:,1]) | ||
| std(jkc[:,1]) | ||
| stderror(mc) | ||
| @assert jk == jkc | ||
| """ | ||
| function jackknife(m::M) where {M<:PHModel} | ||
| uid = unique(m.R.id) | ||
| coefs = zeros(length(uid), length(coef(m))) | ||
| R = deepcopy(m.R) | ||
| P = deepcopy(m.P) | ||
| for i in eachindex(uid) | ||
| Ri, Rj, idxi, idxj = pop(m.R); | ||
| Pi = popat!(m.P, idxi, idxj) | ||
| mi= PHModel(Rj, m.P, m.formula, m.ties, false, m.bh[1:length(Rj.eventtimes),:], nothing) | ||
| fit!(mi, getbasehaz=false) | ||
| coefs[i,:] = coef(mi) | ||
| m.R = push(Ri, Rj) | ||
| push!(Pi, m.P) | ||
| end | ||
| m.R, m.P = R, P | ||
| coefs | ||
| end | ||
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| function jackknife_vcov(m::M) where {M<:PHModel} | ||
| N = nobs(m) | ||
| #comparing estimate with jackknife estimate with bootstrap mean | ||
| jk = jackknife(m); | ||
| covjk = cov(jk) .* (N-1) | ||
| covjk | ||
| end | ||
|
|
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