Estimation of the summary survival curve from the survival rates and the numbers of at-risk individuals extracted from studies of a meta-analysis.
msurv(
study,
time,
n.risk,
surv.rate,
confidence,
correctionFlag = TRUE,
correctionVal = c(0.25, 0.5)
)A numeric vector with the numbering of the studies included in the meta-analysis. The numbering of a study is repeated for each survival probabilities extracted from this study.
A numeric vector with the time at which the survival probabilities are collected.
A numeric vector with the number of at-risk patients in the study for each value of thr time.
A numeric vector with the survival rates collected per study for each value of time.
A text argument indicating the method to calculate the confidence interval of the summary survival probabilities: "Greenwood" or "MonteCarlo".
A logical variable which takes into account if user wants the continuity correaction or not (By default TRUE).
A numeric vector for continuity correction, if you don't want to apply correction pass c(0,0).
list
attach(exampleData)
result <- msurv(study = Study,
time = Time,
n.risk = NbRisk,
surv.rate = Survival,
confidence = "Greenwood",
correctionFlag = FALSE
)
result
#> $verif.data
#> Sstudy check
#> 1 1 1
#> 2 2 1
#> 3 3 1
#> 4 4 1
#> 5 5 1
#> 6 6 1
#> 7 7 1
#> 8 8 1
#> 9 9 1
#> 10 10 1
#> 11 11 1
#> 12 12 1
#> 13 13 1
#> 14 14 1
#> 15 15 1
#> 16 16 1
#> 17 17 1
#> 18 18 1
#> 19 19 1
#> 20 20 1
#> 21 21 1
#> 22 22 1
#> 23 23 1
#> 24 24 1
#> 25 25 1
#> 26 26 1
#> 27 27 1
#>
#> $summary.fixed
#> IndiceTimes PooledSurvivalFE PooledSurvivalICinfFE PooledSurvivalICsupFE
#> [1,] 1 0.9508837 0.93115618 0.9710293
#> [2,] 2 0.8542395 0.82202310 0.8877185
#> [3,] 3 0.7529489 0.71356234 0.7945096
#> [4,] 4 0.6801444 0.63752795 0.7256097
#> [5,] 5 0.6081467 0.56352148 0.6563058
#> [6,] 6 0.5449696 0.49936809 0.5947354
#> [7,] 9 0.4303415 0.38446782 0.4816886
#> [8,] 12 0.3452733 0.30011887 0.3972213
#> [9,] 15 0.2814425 0.23729653 0.3338012
#> [10,] 18 0.2411057 0.19773211 0.2939935
#> [11,] 21 0.2109529 0.16828161 0.2644443
#> [12,] 24 0.1858428 0.14380950 0.2401619
#> [13,] 27 0.1671095 0.12528742 0.2228921
#> [14,] 30 0.1549979 0.11269730 0.2131760
#> [15,] 33 0.1322367 0.08722757 0.2004703
#> [16,] 36 0.1201395 0.07462625 0.1934106
#> [17,] 39 0.1201395 0.07462625 0.1934106
#> [18,] 42 0.1144864 0.06665886 0.1966300
#> [19,] 45 0.1144864 0.06665886 0.1966300
#> [20,] 48 0.1144864 0.06665886 0.1966300
#> nRisk
#> [1,] 1806
#> [2,] 1674
#> [3,] 1467
#> [4,] 1265
#> [5,] 1122
#> [6,] 974
#> [7,] 807
#> [8,] 546
#> [9,] 368
#> [10,] 252
#> [11,] 187
#> [12,] 142
#> [13,] 100
#> [14,] 65
#> [15,] 37
#> [16,] 29
#> [17,] 12
#> [18,] 12
#> [19,] 10
#> [20,] 9
#>
#> $median.fixed
#> 2.5% 97.5%
#> 7.176926 5.937078 8.375936
#>
#> $mean.fixed
#> 2.5% 97.5%
#> 13.46370 11.46318 14.74525
#>
#> $heterogeneity
#> [1] 219.6071244 0.7572659 0.0000000
#>
#> $summary.random
#> IndiceTimes PooledSurvivalRE PooledSurvivalICinfRE PooledSurvivalICsupRE
#> [1,] 1 0.94768647 0.91731470 0.9790638
#> [2,] 2 0.84755282 0.78823478 0.9113348
#> [3,] 3 0.73182809 0.65606515 0.8163402
#> [4,] 4 0.65409564 0.56903170 0.7518757
#> [5,] 5 0.57872161 0.49473929 0.6769600
#> [6,] 6 0.50184228 0.41034422 0.6137425
#> [7,] 9 0.38269038 0.29711268 0.4929171
#> [8,] 12 0.29890154 0.22167479 0.4030324
#> [9,] 15 0.23629264 0.16877051 0.3308292
#> [10,] 18 0.20208143 0.14274382 0.2860853
#> [11,] 21 0.17082971 0.11580178 0.2520064
#> [12,] 24 0.15126442 0.10079984 0.2269937
#> [13,] 27 0.13757394 0.09019805 0.2098337
#> [14,] 30 0.12300453 0.07677350 0.1970747
#> [15,] 33 0.10536383 0.06049565 0.1835097
#> [16,] 36 0.10074068 0.05720945 0.1773952
#> [17,] 39 0.10074068 0.05720945 0.1773952
#> [18,] 42 0.08499342 0.03811229 0.1895420
#> [19,] 45 0.08499342 0.03811229 0.1895420
#> [20,] 48 0.08499342 0.03811229 0.1895420
#> nRisk
#> [1,] 1806
#> [2,] 1674
#> [3,] 1467
#> [4,] 1265
#> [5,] 1122
#> [6,] 974
#> [7,] 807
#> [8,] 546
#> [9,] 368
#> [10,] 252
#> [11,] 187
#> [12,] 142
#> [13,] 100
#> [14,] 65
#> [15,] 37
#> [16,] 29
#> [17,] 12
#> [18,] 12
#> [19,] 10
#> [20,] 9
#>
#> $median.random
#> 2.5% 97.5%
#> 6.046385 4.815541 8.474948
#>
#> $mean.random
#> 2.5% 97.5%
#> 11.92947 9.13597 14.39214
#>