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sidiwang committed Sep 13, 2024
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[![License: GPL v2](https://img.shields.io/badge/License-GPL_v2-blue.svg)](https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html)
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93 changes: 47 additions & 46 deletions README.md
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developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/)
[![Codecov test
coverage](https://codecov.io/gh/sidiwang/snSMART/branch/main/graph/badge.svg)](https://app.codecov.io/gh/sidiwang/snSMART?branch=main)
[![DOI](https://joss.theoj.org/papers/10.21105/joss.06971/status.svg)](https://doi.org/10.21105/joss.06971)
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The aim of the **snSMART** R package is to consolidate data simulation,
@@ -48,7 +49,7 @@ install.packages("snSMART", repos = "http://cran.us.r-project.org")

##
## The downloaded binary packages are in
## /var/folders/5_/sp2r7r_s5snf4hq634xmk_0r0000gn/T//RtmpUxY3P4/downloaded_packages
## /var/folders/5_/sp2r7r_s5snf4hq634xmk_0r0000gn/T//RtmpUpvbHg/downloaded_packages

``` r
library(snSMART)
@@ -110,33 +111,33 @@ summary(BJSM_result)
##
## Treatment Effects Estimate:
## Estimate Std. Error C.I. CI low CI high
## trtA 0.3733798 0.1532599 0.95 0.1879501 0.7281596
## trtB 0.4185251 0.1646755 0.95 0.1377496 0.7658878
## trtC 0.6694094 0.1044533 0.95 0.4533836 0.8364925
## trtA 0.4230557 0.10984677 0.95 0.2132406 0.6239648
## trtB 0.4621068 0.09676214 0.95 0.2859294 0.6378900
## trtC 0.5949919 0.04873058 0.95 0.5357735 0.6742898
##
## Differences between Treatments:
## Estimate Std.Error C.I. CI low CI high
## diffAB -0.04514528 0.2534023 0.95 -0.5669267 0.377003340
## diffBC -0.25088433 0.1648132 0.95 -0.5241105 0.093336459
## diffAC -0.29602961 0.1676356 0.95 -0.5361779 0.002146219
## Estimate Std.Error C.I. CI low CI high
## diffAB -0.03905106 0.1733779 0.95 -0.3686263 0.22405873
## diffBC -0.13288514 0.1246969 0.95 -0.3755066 0.07647332
## diffAC -0.17193620 0.1133842 0.95 -0.3321949 0.04989511
##
## Linkage Parameter Estimate:
## Estimate Std. Error C.I. CI low CI high
## beta0A 0.9109306 0.09415977 0.95 0.7450933 0.9991757
## beta0B 0.9474557 0.05466744 0.95 0.8546296 0.9998542
## beta0C 0.6844260 0.25597435 0.95 0.1968036 0.9921257
## beta1A 1.3743002 0.40896514 0.95 1.0046594 2.9088154
## beta1B 1.6303701 0.81305930 0.95 1.0023232 3.8184414
## beta1C 1.2112592 0.18514509 0.95 1.0012300 1.6548299
## beta0A 0.9377270 0.07330169 0.95 0.7715834 0.9999638
## beta0B 0.8822049 0.08253566 0.95 0.7357460 0.9998799
## beta0C 0.7042976 0.26361834 0.95 0.1427238 0.9771399
## beta1A 1.3582895 0.27307278 0.95 1.0028447 1.9003715
## beta1B 1.3271310 0.29322491 0.95 1.0072391 2.2666544
## beta1C 1.3889213 0.19685318 0.95 1.0015164 1.7286500
##
## Expected Response Rate of Dynamic Treatment Regimens (DTR):
## Estimate Std. Error C.I. CI low CI high
## rep_AB 0.4490128 0.13354447 0.95 0.1833142 0.6635111
## rep_AC 0.5858904 0.10180160 0.95 0.4046741 0.7529446
## rep_BA 0.4754814 0.12128590 0.95 0.2514877 0.6599729
## rep_BC 0.6272426 0.09956371 0.95 0.4679389 0.8323915
## rep_CA 0.6280401 0.11172644 0.95 0.3704172 0.7754331
## rep_CB 0.6315693 0.12178323 0.95 0.3518751 0.8164481
## rep_AB 0.5003874 0.07678636 0.95 0.3585359 0.6151457
## rep_AC 0.5671207 0.07019227 0.95 0.4567067 0.6971029
## rep_BA 0.4983502 0.09710728 0.95 0.3015048 0.6378734
## rep_BC 0.5780166 0.09550426 0.95 0.4319781 0.7034776
## rep_CA 0.6077879 0.10240957 0.95 0.4230910 0.7724611
## rep_CB 0.6205831 0.08853430 0.95 0.4310405 0.8091465

`LPJSM_binary`: Here, we call the LPJSM_binary mirroring our example for
the BJSM_binary above.
@@ -261,24 +262,24 @@ summary(result2)
##
## Treatment Effects Estimate:
## Estimate Std. Error C.I. CI low CI high
## trtA 0.3015 0.04856 0.95 0.2064 0.3960
## trtB 0.4735 0.03939 0.95 0.3957 0.5492
## trtC 0.6808 0.04373 0.95 0.5908 0.7638
## trtA 0.3010 0.04901 0.95 0.2064 0.3973
## trtB 0.4734 0.03969 0.95 0.3967 0.5518
## trtC 0.6829 0.04032 0.95 0.6039 0.7587
##
## Differences between Treatments:
## Estimate Std.Error C.I. CI low CI high
## diffAB -0.1719 0.06223 0.95 -0.2955 -0.05129
## diffBC -0.2073 0.05767 0.95 -0.3185 -0.09348
## diffAC -0.3793 0.06379 0.95 -0.5018 -0.25274
## diffAB -0.1724 0.06288 0.95 -0.2934 -0.04701
## diffBC -0.2095 0.05548 0.95 -0.3176 -0.10193
## diffAC -0.3819 0.06203 0.95 -0.5016 -0.25930
##
## Linkage Parameter Estimate:
## Estimate Std. Error C.I. CI low CI high
## beta0A 0.8700 0.1105 0.95 0.6625 1.0000
## beta0B 0.7174 0.1147 0.95 0.5010 0.9568
## beta0C 0.8710 0.1267 0.95 0.6192 1.0000
## beta1A 1.4728 0.3595 0.95 1.0000 2.1657
## beta1B 1.3606 0.1704 0.95 1.0375 1.6863
## beta1C 1.4550 0.0977 0.95 1.2738 1.6569
## beta0A 0.8687 0.11044 0.95 0.6615 1.0000
## beta0B 0.7141 0.11250 0.95 0.4944 0.9419
## beta0C 0.8718 0.12633 0.95 0.6187 1.0000
## beta1A 1.4751 0.36568 0.95 1.0000 2.1793
## beta1B 1.3613 0.16992 0.95 1.0266 1.6774
## beta1C 1.4494 0.08872 0.95 1.2860 1.6265

`BJSM_c`: Below, we call the function assuming the mean and standard
deviation of the normal prior being 50 and 50 for all three treatments,
@@ -297,20 +298,20 @@ summary(BJSM_result)

##
## Parameter Estimation:
## Estimate CI CI_low CI_high
## V1[1,1] 111.0169 0.95 60.701765 168.5941
## V1[2,1] 85.2106 0.95 44.885297 132.4085
## V1[1,2] 85.2106 0.95 44.885297 132.4085
## V1[2,2] 77.4065 0.95 43.146839 117.7926
## V2[1,1] 123.2723 0.95 66.132083 193.6889
## V2[2,1] 28.6508 0.95 -16.647146 75.8023
## V2[1,2] 28.6508 0.95 -16.647146 75.8023
## V2[2,2] 106.9160 0.95 55.412731 167.4823
## phi1 0.1818 0.95 0.000246 0.3768
## phi3 3.9991 0.95 2.705726 5.2487
## xi_[A] 51.1377 0.95 47.256453 54.9003
## xi_[B] 62.0380 0.95 58.063443 65.5587
## xi_[C] 69.0069 0.95 65.538008 72.9675
## Estimate CI CI_low CI_high
## V1[1,1] 111.4730 0.95 6.127e+01 170.443
## V1[2,1] 85.5731 0.95 4.313e+01 131.885
## V1[1,2] 85.5731 0.95 4.313e+01 131.885
## V1[2,2] 77.7046 0.95 4.287e+01 119.640
## V2[1,1] 123.2901 0.95 6.477e+01 194.723
## V2[2,1] 29.2337 0.95 -1.714e+01 78.510
## V2[1,2] 29.2337 0.95 -1.714e+01 78.510
## V2[2,2] 107.6312 0.95 5.585e+01 171.342
## phi1 0.1817 0.95 2.822e-04 0.387
## phi3 4.0143 0.95 2.807e+00 5.400
## xi_[A] 51.1199 0.95 4.716e+01 54.890
## xi_[B] 62.0682 0.95 5.819e+01 65.932
## xi_[C] 68.9650 0.95 6.520e+01 72.650

This R package will continue to be updated as more snSMART designs and
methods are developed. We hope that this package translates snSMART

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