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Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview > # * https://testthat.r-lib.org/articles/special-files.html > > library(testthat) > library(SEQ) > > test_check("SEQ") Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed SEQuential process completed in 4.48 seconds : Initialized with: Outcome covariates: outcome~tx_init_bas+followup+followup_sq+trial+trial_sq+sex+N_bas+L_bas+P_bas+tx_init_bas*followup Numerator covariates: NA Denominator covariates: NA Full Model Information ========================================== Outcome Model ==================================================== Coefficients and Weighting: Call: fastglm.default(x = X, y = y, family = quasibinomial(), method = params@fastglm.method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -6.859e+00 5.680e-01 -12.075 < 2e-16 *** tx_init_bas1 2.253e-01 5.102e-02 4.416 1.01e-05 *** followup 3.538e-02 3.797e-03 9.319 < 2e-16 *** followup_sq -1.599e-04 6.637e-05 -2.409 0.016013 * trial 4.472e-02 1.125e-02 3.975 7.05e-05 *** trial_sq 5.762e-04 1.003e-04 5.747 9.11e-09 *** sex1 1.270e-01 2.596e-02 4.894 9.91e-07 *** N_bas 3.287e-03 2.590e-03 1.269 0.204430 L_bas -1.385e-02 1.430e-02 -0.969 0.332696 P_bas 2.009e-01 5.957e-02 3.373 0.000744 *** tx_init_bas1:followup -1.704e-03 1.948e-03 -0.875 0.381798 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for quasibinomial family taken to be 1.013725) Null deviance: 59179 on 248484 degrees of freedom Residual deviance: 57177 on 248474 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 7 Diagnostic Tables ================================================== Unique Outcome Table: |tx_init_bas | outcome| n| |:-----------|-------:|---:| |0 | 1| 203| |1 | 1| 185| Non-Unique Outcome Table: |tx_init_bas | outcome| n| |:-----------|-------:|----:| |0 | 1| 1928| |1 | 1| 4432| Expanding Data... Expansion Successful Moving forward with dose-response analysis dose-response model created successfully Completed Expanding Data... Expansion Successful Moving forward with dose-response analysis dose-response model created successfully Completed Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed SEQuential process completed in 6.04 seconds : Initialized with: Outcome covariates: outcome~tx_init_bas+followup+followup_sq+trial+trial_sq+sex+N_bas+L_bas+P_bas+tx_init_bas*followup Numerator covariates: tx_init~sex+N_bas+L_bas+P_bas+followup+followup_sq+trial+trial_sq Denominator covariates: tx_init~sex+N+L+P+N_bas+L_bas+P_bas+followup+followup_sq+trial+trial_sq Full Model Information ========================================== Outcome Model ==================================================== Coefficients and Weighting: Call: fastglm.default(x = X, y = y, family = quasibinomial(), weights = weight, method = params@fastglm.method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -9.084e+00 1.020e+00 -8.903 < 2e-16 *** tx_init_bas1 3.754e-01 1.024e-01 3.664 0.000248 *** followup 1.159e-02 1.452e-02 0.798 0.424678 followup_sq 3.851e-05 1.537e-04 0.251 0.802152 trial 6.687e-02 1.997e-02 3.349 0.000812 *** trial_sq 5.847e-04 1.646e-04 3.552 0.000382 *** sex1 8.200e-02 4.264e-02 1.923 0.054507 . N_bas 4.808e-03 4.303e-03 1.117 0.263932 L_bas 1.403e-02 2.013e-02 0.697 0.485845 P_bas 4.462e-01 1.067e-01 4.180 2.92e-05 *** tx_init_bas1:followup 1.934e-02 1.462e-02 1.323 0.185933 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for quasibinomial family taken to be 1.01505) Null deviance: 22205 on 96250 degrees of freedom Residual deviance: 21176 on 96240 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 7 Weight Information ============================================= Treatment Lag = 0 Treatment = 0 Model ==================================== Denominator ========================== Call: fastglm.default(x = X, y = y, family = quasibinomial(), method = params@fastglm.method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -2.1964004 0.8389945 -2.618 0.00886 ** sex1 0.1115039 0.0448359 2.487 0.01289 * N 0.0138112 0.0042418 3.256 0.00113 ** L 0.2018464 0.0939947 2.147 0.03177 * P 0.2493387 0.1746751 1.427 0.15347 N_bas 0.0054225 0.0042524 1.275 0.20227 L_bas -0.1994854 0.1209594 -1.649 0.09913 . P_bas -0.1918628 0.1796765 -1.068 0.28562 followup 0.0031087 0.0291996 0.106 0.91522 followup_sq 0.0006775 0.0004754 1.425 0.15418 trial -0.0036625 0.0165739 -0.221 0.82511 trial_sq 0.0001652 0.0001616 1.022 0.30692 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for quasibinomial family taken to be 1.001142) Null deviance: 14601 on 16033 degrees of freedom Residual deviance: 14565 on 16022 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 4 Treatment Lag = 1 Treatment = 1 Model ==================================== Denominator ========================== Call: fastglm.default(x = X, y = y, family = quasibinomial(), method = params@fastglm.method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.624e+00 7.925e-01 3.311 0.000932 *** sex1 -1.424e-02 3.376e-02 -0.422 0.673234 N 3.487e-03 3.385e-03 1.030 0.302865 L 1.719e-01 3.874e-02 4.437 9.15e-06 *** P -4.534e-01 1.121e-01 -4.043 5.27e-05 *** N_bas 3.436e-03 3.378e-03 1.017 0.309153 L_bas -2.988e-02 5.997e-02 -0.498 0.618303 P_bas 4.726e-01 1.182e-01 3.997 6.42e-05 *** followup -6.244e-02 1.491e-02 -4.188 2.82e-05 *** followup_sq 1.511e-05 1.395e-04 0.108 0.913751 trial 7.136e-03 1.557e-02 0.458 0.646638 trial_sq -2.722e-04 1.489e-04 -1.829 0.067448 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for quasibinomial family taken to be 1.004322) Null deviance: 30197 on 77511 degrees of freedom Residual deviance: 30046 on 77500 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 6 Weights: Min: 0.5060308 Max: 3.101522 StDev: 0.04174202 P01: 0.8809239 P25: 0.9894742 P50: 1 P75: 1.009571 P99: 1.094614 Diagnostic Tables ================================================== Unique Outcome Table: |tx_init_bas | outcome| n| |:-----------|-------:|---:| |1 | 1| 153| |0 | 1| 50| Non-Unique Outcome Table: |tx_init_bas | outcome| n| |:-----------|-------:|----:| |1 | 1| 2157| |0 | 1| 222| Unique Switch Table: |switch | n| |:------|-----:| |FALSE | 11127| |TRUE | 1053| Non-Unique Switch Table: |switch | n| |:------|-----:| |FALSE | 96251| |TRUE | 6498| Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis Expanding Data... Expansion Successful Moving forward with ITT analysis Completed Expanding Data... Expansion Successful Moving forward with censoring analysis Bootstrapping with 80 % of data 2 times censoring model created successfully Creating Survival curves Scale for colour is already present. Adding another scale for colour, which will replace the existing scale. Completed Scale for colour is already present. Adding another scale for colour, which will replace the existing scale. Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed SEQuential process completed in 3.68 seconds : Initialized with: Outcome covariates: outcome~tx_init_bas+followup+followup_sq+trial+trial_sq+sex+N_bas+L_bas+P_bas+tx_init_bas*followup Numerator covariates: NA Denominator covariates: NA Full Model Information ========================================== Outcome Model ==================================================== Coefficients and Weighting: Call: fastglm.default(x = X, y = y, family = quasibinomial(), method = params@fastglm.method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -40.065915 422.719875 -0.095 0.92449 tx_init_bas1 0.894545 0.522056 1.714 0.08662 . tx_init_bas2 -3.096917 0.590889 -5.241 1.60e-07 *** followup 0.170743 0.040414 4.225 2.39e-05 *** followup_sq -0.005646 0.001096 -5.153 2.57e-07 *** trial 0.381544 0.088025 4.334 1.46e-05 *** trial_sq -0.005852 0.001033 -5.664 1.48e-08 *** sex1 17.857596 422.696985 0.042 0.96630 N_bas 0.051540 0.019390 2.658 0.00786 ** L_bas 0.817806 0.143448 5.701 1.19e-08 *** P_bas 1.361443 0.456183 2.984 0.00284 ** tx_init_bas1:followup -0.642974 0.153274 -4.195 2.73e-05 *** tx_init_bas2:followup 0.120583 0.027788 4.339 1.43e-05 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for quasibinomial family taken to be 0.3107568) Null deviance: 660.77 on 128156 degrees of freedom Residual deviance: 534.30 on 128144 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 24 Diagnostic Tables ================================================== Unique Outcome Table: |tx_init_bas | outcome| n| |:-----------|-------:|--:| |0 | 1| 1| |2 | 1| 1| |1 | 1| 1| Non-Unique Outcome Table: |tx_init_bas | outcome| n| |:-----------|-------:|--:| |0 | 1| 16| |2 | 1| 16| |1 | 1| 4| Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed SEQuential process completed in 2.86 seconds : Initialized with: Outcome covariates: outcome~tx_init_bas+followup+followup_sq+trial+trial_sq+sex+tx_init_bas*followup Numerator covariates: tx_init~sex+time+time_sq Denominator covariates: tx_init~sex+N+L+P+time+time_sq Full Model Information ========================================== Outcome Model ==================================================== Coefficients and Weighting: Call: fastglm.default(x = X, y = y, family = quasibinomial(), weights = weight, method = params@fastglm.method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -460.79040 3633.11449 -0.127 0.899 tx_init_bas1 28.36046 3602.24478 0.008 0.994 tx_init_bas2 -118.33850 4774.20075 -0.025 0.980 followup 3.53205 615.94850 0.006 0.995 followup_sq -0.28416 0.02613 -10.875 <2e-16 *** trial 24.33871 1.54161 15.788 <2e-16 *** trial_sq -0.36210 0.02296 -15.773 <2e-16 *** sex1 19.72139 471.85195 0.042 0.967 tx_init_bas1:followup -2.75720 615.94846 -0.004 0.996 tx_init_bas2:followup 8.65487 633.43948 0.014 0.989 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for quasibinomial family taken to be 0.006580056) Null deviance: 82.063 on 42296 degrees of freedom Residual deviance: 40.100 on 42287 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 28 Weight Information ============================================= Treatment Lag = 0 Treatment = 0 Model ==================================== Denominator ========================== Nested Model: Treatment = 1 ========= Call: fastglm.default(x = X, y = ybin, family = family, method = method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -6.1573661 4.5273800 -1.360 0.174 sex1 0.2235736 0.2032074 1.100 0.271 N -0.0133612 0.0210610 -0.634 0.526 L -0.1302414 0.0920059 -1.416 0.157 P 0.3745089 0.4774276 0.784 0.433 time 0.1139056 0.0863576 1.319 0.187 time_sq -0.0009750 0.0006659 -1.464 0.143 (Dispersion parameter for quasibinomial family taken to be 1.006216) Null deviance: 741.08 on 1182 degrees of freedom Residual deviance: 728.00 on 1176 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 5 Nested Model: Treatment = 2 ========= Call: fastglm.default(x = X, y = ybin, family = family, method = method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -3.0960751 4.7492673 -0.652 0.5146 sex1 0.3534343 0.2109185 1.676 0.0941 . N -0.0102324 0.0219052 -0.467 0.6405 L 0.0103966 0.0823995 0.126 0.8996 P 0.0314063 0.5020658 0.063 0.9501 time 0.0330558 0.0900849 0.367 0.7137 time_sq -0.0002855 0.0006856 -0.416 0.6772 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for quasibinomial family taken to be 1.004432) Null deviance: 699.62 on 1182 degrees of freedom Residual deviance: 688.41 on 1176 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 5 Treatment Lag = 1 Treatment = 1 Model ==================================== Denominator ========================== Nested Model: Treatment = 1 ========= Call: fastglm.default(x = X, y = ybin, family = family, method = method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.067e+00 5.211e+00 0.205 0.838 sex1 9.544e-02 1.834e-01 0.520 0.603 N 3.205e-03 1.820e-02 0.176 0.860 L -9.328e-04 5.605e-02 -0.017 0.987 P 2.208e-01 5.528e-01 0.399 0.690 time 1.477e-02 9.823e-02 0.150 0.880 time_sq 9.222e-05 7.132e-04 0.129 0.897 (Dispersion parameter for quasibinomial family taken to be 1.002066) Null deviance: 1011.3 on 2455 degrees of freedom Residual deviance: 1010.1 on 2449 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 5 Nested Model: Treatment = 2 ========= Call: fastglm.default(x = X, y = ybin, family = family, method = method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 6.0684132 7.4996437 0.809 0.419 sex1 -0.1873988 0.2682454 -0.699 0.485 N -0.0018731 0.0265776 -0.070 0.944 L -0.0260750 0.0900972 -0.289 0.772 P -1.0423959 0.7989424 -1.305 0.192 time -0.1557571 0.1416047 -1.100 0.271 time_sq 0.0006375 0.0010422 0.612 0.541 (Dispersion parameter for quasibinomial family taken to be 1.003276) Null deviance: 556.56 on 2455 degrees of freedom Residual deviance: 552.92 on 2449 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 6 Treatment Lag = 2 Treatment = 2 Model ==================================== Denominator ========================== Nested Model: Treatment = 1 ========= Call: fastglm.default(x = X, y = ybin, family = family, method = method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -12.436421 7.385435 -1.684 0.0923 . sex1 0.563480 0.268322 2.100 0.0358 * N -0.030240 0.026924 -1.123 0.2615 L 0.241511 0.105948 2.280 0.0227 * P 0.919744 0.778131 1.182 0.2373 time 0.182061 0.141787 1.284 0.1993 time_sq -0.001910 0.001087 -1.758 0.0789 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for quasibinomial family taken to be 0.9638027) Null deviance: 535.95 on 2336 degrees of freedom Residual deviance: 520.83 on 2330 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 7 Nested Model: Treatment = 2 ========= Call: fastglm.default(x = X, y = ybin, family = family, method = method) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 5.9274608 5.4667749 1.084 0.27836 sex1 -0.5842318 0.1932441 -3.023 0.00253 ** N -0.0036972 0.0195214 -0.189 0.84980 L -0.0252389 0.0673760 -0.375 0.70799 P -0.2937206 0.5798381 -0.507 0.61251 time -0.0450474 0.1037497 -0.434 0.66419 time_sq 0.0002942 0.0007572 0.388 0.69771 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for quasibinomial family taken to be 1.004845) Null deviance: 928.74 on 2336 degrees of freedom Residual deviance: 918.68 on 2330 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 6 Weights: Min: 0.2478252 Max: 6.309442 StDev: 0.1998333 P01: 0.757827 P25: 0.97187 P50: 0.9987108 P75: 1.020873 P99: 1.623825 Diagnostic Tables ================================================== Unique Outcome Table: |tx_init_bas | outcome| n| |:-----------|-------:|--:| |1 | 1| 1| Non-Unique Outcome Table: |tx_init_bas | outcome| n| |:-----------|-------:|--:| |1 | 1| 4| Unique Switch Table: |switch | n| |:------|----:| |FALSE | 5515| |TRUE | 461| Non-Unique Switch Table: |switch | n| |:------|-----:| |FALSE | 42297| |TRUE | 2713| Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed Expanding Data... Expansion Successful Moving forward with dose-response analysis Bootstrapping with 80 % of data 2 times dose-response model created successfully Completed Expanding Data... Expansion Successful Moving forward with dose-response analysis Bootstrapping with 80 % of data 2 times dose-response model created successfully Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Creating Survival curves Scale for colour is already present. Adding another scale for colour, which will replace the existing scale. Completed Expanding Data... Expansion Successful Moving forward with ITT analysis Bootstrapping with 80 % of data 2 times ITT model created successfully Creating Survival curves Scale for colour is already present. Adding another scale for colour, which will replace the existing scale. Completed Expanding Data... Expansion Successful Moving forward with ITT analysis ITT model created successfully Completed Expanding Data... Expansion Successful Moving forward with censoring analysis censoring model created successfully Completed [ FAIL 0 | WARN 0 | SKIP 0 | PASS 88 ] > > proc.time() user system elapsed 221.26 64.73 279.00