Last updated on 2021-03-04 00:48:05 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.2.1 | 28.74 | 356.37 | 385.11 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.2.1 | 19.91 | 261.72 | 281.63 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.2.2 | 453.07 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 0.2.2 | 443.02 | NOTE | |||
| r-devel-windows-ix86+x86_64 | 0.2.1 | 66.00 | 404.00 | 470.00 | OK | |
| r-patched-linux-x86_64 | 0.2.1 | 19.96 | 336.28 | 356.24 | OK | |
| r-patched-solaris-x86 | 0.2.2 | 523.50 | NOTE | |||
| r-release-linux-x86_64 | 0.2.1 | 18.66 | 334.03 | 352.69 | OK | |
| r-release-macos-x86_64 | 0.2.1 | NOTE | ||||
| r-release-windows-ix86+x86_64 | 0.2.1 | 68.00 | 494.00 | 562.00 | OK | |
| r-oldrel-macos-x86_64 | 0.2.1 | ERROR | ||||
| r-oldrel-windows-ix86+x86_64 | 0.2.1 | 59.00 | 455.00 | 514.00 | ERROR |
Version: 0.2.2
Check: package dependencies
Result: NOTE
Imports includes 29 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable. Move as many as possible to Suggests and
use conditionally.
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.2.2
Check: dependencies in R code
Result: NOTE
Namespaces in Imports field not imported from:
‘flexsurv’ ‘nlme’ ‘tibble’ ‘tidyverse’ ‘tm’
All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86
Version: 0.2.2
Check: installed package size
Result: NOTE
installed size is 5.1Mb
sub-directories of 1Mb or more:
extdata 3.8Mb
Flavor: r-patched-solaris-x86
Version: 0.2.1
Check: dependencies in R code
Result: NOTE
Namespaces in Imports field not imported from:
‘flexsurv’ ‘nlme’ ‘tibble’ ‘tidyverse’ ‘tm’
All declared Imports should be used.
Flavors: r-release-macos-x86_64, r-oldrel-macos-x86_64
Version: 0.2.1
Check: R code for possible problems
Result: NOTE
plot_return_residual_cox: no visible global function definition for
‘plot’
plot_return_residual_survival: no visible global function definition
for ‘plot’
Undefined global functions or variables:
plot
Consider adding
importFrom("graphics", "plot")
to your NAMESPACE file.
Flavors: r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64
Version: 0.2.1
Check: examples
Result: ERROR
Running examples in ‘packDAMipd-Ex.R’ failed
The error most likely occurred in:
> ### Name: microcosting_liquids_long
> ### Title: Function to estimate the cost of liquids when IPD is in long
> ### format
> ### Aliases: microcosting_liquids_long
>
> ### ** Examples
>
> med_costs_file <- system.file("extdata", "average_unit_costs_med_brand.csv",
+ package = "packDAMipd")
> data_file <- system.file("extdata", "medication_liq.xlsx",
+ package = "packDAMipd")
> ind_part_data <- load_trial_data(data_file)
> med_costs <- load_trial_data(med_costs_file)
> conv_file <- system.file("extdata", "Med_calc.xlsx",
+ package = "packDAMipd")
> table <- load_trial_data(conv_file)
> names <- colnames(ind_part_data)
> ending <- length(names)
> ind_part_data_long <- tidyr::gather(ind_part_data, measurement, value,
+ names[2]:names[ending], factor_key = TRUE)
> the_columns <- c("measurement", "value")
> res <- microcosting_liquids_long(the_columns,
+ ind_part_data_long = ind_part_data_long,
+ name_med = "liq_name", brand_med = NULL, dose_med = "liq_strength",
+ unit_med = NULL, bottle_size = "liq_bottle_size",bottle_size_unit = NULL,
+ bottle_lasts = "liq_lasts",bottle_lasts_unit = NULL,preparation_dose = NULL,
+ preparation_unit = NULL,timeperiod = "4 months",unit_cost_data = med_costs,
+ unit_cost_column = "UnitCost",cost_calculated_per = "Basis",
+ strength_column = "Strength",list_of_code_names = NULL,
+ list_of_code_brand = NULL,list_of_code_dose_unit = NULL,
+ list_of_code_bottle_size_unit = NULL,list_of_code_bottle_lasts_unit = NULL,
+ list_preparation_dose_unit = NULL,eqdose_covtab = table,
+ basis_strength_unit = NULL)
Error in microcosting_liquids_wide(ind_part_data_wide, name_med, brand_med, :
The used dosage is not in costing table
Calls: microcosting_liquids_long -> microcosting_liquids_wide
Execution halted
Flavors: r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64
Version: 0.2.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [71s/72s]
Running the tests in ‘tests/testthat.R’ failed.
Last 13 lines of output:
ans$brand not equal to "a".
'current' is not a factor
── Failure (test-help_cost_analysis_functions.R:15:4): testing to get the subset of data compared to list of string ──
ans$brand not equal to "a".
'current' is not a factor
── Failure (test-help_cost_analysis_functions.R:24:3): testing to get the subset of data compared to list of string ──
ans$xx not equal to c("bb", "aa").
'current' is not a factor
── Failure (test-help_parameter_estimation_survival.R:94:3): testing creating a new dataset based on given one ──
unique(new$check) not equal to "no".
'current' is not a factor
[ FAIL 9 | WARN 0 | SKIP 0 | PASS 994 ]
Error: Test failures
Execution halted
Flavor: r-oldrel-macos-x86_64
Version: 0.2.1
Check: tests
Result: ERROR
Running 'testthat.R' [119s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(packDAMipd)
>
> test_check("packDAMipd")
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
Call:
lm(formula = gre ~ gpa, data = dataset)
Residuals:
Min 1Q Median 3Q Max
-302.394 -62.789 -2.206 68.506 283.438
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 192.30 47.92 4.013 7.15e-05 ***
gpa 116.64 14.05 8.304 1.60e-15 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 106.8 on 398 degrees of freedom
Multiple R-squared: 0.1477, Adjusted R-squared: 0.1455
F-statistic: 68.95 on 1 and 398 DF, p-value: 1.596e-15
ASSESSMENT OF THE LINEAR MODEL ASSUMPTIONS
USING THE GLOBAL TEST ON 4 DEGREES-OF-FREEDOM:
Level of Significance = 0.05
Call:
gvlma::gvlma(x = fit)
Value p-value Decision
Global Stat 2.7853 0.5944 Assumptions acceptable.
Skewness 0.1510 0.6975 Assumptions acceptable.
Kurtosis 0.9735 0.3238 Assumptions acceptable.
Link Function 0.3578 0.5497 Assumptions acceptable.
Heteroscedasticity 1.3030 0.2537 Assumptions acceptable.
[1] "i= 1 and j = 1"
[1] "i= 1 and j = 2"
[1] "i= 2 and j = 1"
[1] "i= 2 and j = 2"
[1] "i= 3 and j = 1"
[1] "i= 3 and j = 2"
$stats
[,1] [,2]
[1,] 35.62186 37.20490
[2,] 47.35844 48.63362
[3,] 52.71848 51.79091
[4,] 55.90675 58.49112
[5,] 63.60830 65.19133
$n
[1] 109 91
$conf
[,1] [,2]
[1,] 51.42481 50.15822
[2,] 54.01215 53.42360
$out
numeric(0)
$group
numeric(0)
$names
[1] "female" "male"
Call:
lm(formula = admit ~ gpa, data = dataset)
Residuals:
Min 1Q Median 3Q Max
-0.4507 -0.3312 -0.2531 0.5908 0.8942
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.42238 0.20606 -2.050 0.041037 *
gpa 0.21826 0.06041 3.613 0.000341 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4592 on 398 degrees of freedom
Multiple R-squared: 0.03176, Adjusted R-squared: 0.02933
F-statistic: 13.05 on 1 and 398 DF, p-value: 0.0003412
ASSESSMENT OF THE LINEAR MODEL ASSUMPTIONS
USING THE GLOBAL TEST ON 4 DEGREES-OF-FREEDOM:
Level of Significance = 0.05
Call:
gvlma::gvlma(x = fit)
Value p-value Decision
Global Stat 66.0026 1.582e-13 Assumptions NOT satisfied!
Skewness 37.1456 1.096e-09 Assumptions NOT satisfied!
Kurtosis 28.0492 1.183e-07 Assumptions NOT satisfied!
Link Function 0.5683 4.509e-01 Assumptions acceptable.
Heteroscedasticity 0.2394 6.247e-01 Assumptions acceptable.
Start: AIC=6.76
expression ~ temperature + treatment
Df Sum of Sq RSS AIC
- treatment 4 5.255 25.529 4.523
<none> 20.274 6.762
- temperature 1 40.306 60.581 32.127
Step: AIC=4.52
expression ~ temperature
Df Sum of Sq RSS AIC
<none> 25.529 4.523
+ treatment 4 5.255 20.274 6.762
- temperature 1 219.509 245.038 59.063
Call:
lm(formula = expression ~ temperature + treatment, data = dataset)
Residuals:
Min 1Q Median 3Q Max
-2.3417 -0.5409 0.0743 0.5725 1.6273
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -8.0714 1.5734 -5.130 5.95e-05 ***
temperature 0.8168 0.1329 6.146 6.59e-06 ***
treatmentB 0.2796 0.6539 0.428 0.674
treatmentC 0.4602 0.6573 0.700 0.492
treatmentD 1.3629 0.6814 2.000 0.060 .
treatmentE 1.7445 1.1304 1.543 0.139
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.033 on 19 degrees of freedom
Multiple R-squared: 0.9173, Adjusted R-squared: 0.8955
F-statistic: 42.13 on 5 and 19 DF, p-value: 1.232e-09
ASSESSMENT OF THE LINEAR MODEL ASSUMPTIONS
USING THE GLOBAL TEST ON 4 DEGREES-OF-FREEDOM:
Level of Significance = 0.05
Call:
gvlma::gvlma(x = fit)
Value p-value Decision
Global Stat 11.02282 0.02631 Assumptions NOT satisfied!
Skewness 0.44187 0.50622 Assumptions acceptable.
Kurtosis 0.01247 0.91109 Assumptions acceptable.
Link Function 9.42560 0.00214 Assumptions NOT satisfied!
Heteroscedasticity 1.14288 0.28504 Assumptions acceptable.
Start: AIC=486.34
admit ~ gpa + gre
Df Deviance AIC
<none> 480.34 486.34
- gpa 1 486.06 490.06
- gre 1 486.97 490.97
[1] "i= 1 and j = 1"
[1] "i= 1 and j = 2"
[1] "i= 2 and j = 1"
[1] "i= 2 and j = 2"
[1] "i= 3 and j = 1"
[1] "i= 3 and j = 2"
[1] "i= 1 and j = 1"
[1] "i= 1 and j = 2"
[1] "i= 2 and j = 1"
[1] "i= 2 and j = 2"
[1] "i= 3 and j = 1"
[1] "i= 3 and j = 2"
[1] "i= 1 and j = 1"
[1] "i= 1 and j = 2"
[1] "i= 2 and j = 1"
[1] "i= 2 and j = 2"
[1] "i= 3 and j = 1"
[1] "i= 3 and j = 2"
[1] "i= 1 and j = 1"
[1] "i= 1 and j = 2"
[1] "i= 2 and j = 1"
[1] "i= 2 and j = 2"
[1] "i= 3 and j = 1"
[1] "i= 3 and j = 2"
[1] "i= 1 and j = 1"
[1] "i= 1 and j = 2"
$stats
[,1] [,2]
[1,] 36.71911 35.20799
[2,] 48.19627 47.82501
[3,] 52.18580 52.30597
[4,] 58.49431 56.37400
[5,] 64.80282 63.29169
$n
[1] 91 109
$conf
[,1] [,2]
[1,] 50.48015 51.01219
[2,] 53.89145 53.59974
$out
numeric(0)
$group
numeric(0)
$names
[1] "male" "female"
$stats
[,1] [,2]
[1,] 36.71911 35.20799
[2,] 48.19627 47.82501
[3,] 52.18580 52.30597
[4,] 58.49431 56.37400
[5,] 64.80282 63.29169
$n
[1] 91 109
$conf
[,1] [,2]
[1,] 50.48015 51.01219
[2,] 53.89145 53.59974
$out
numeric(0)
$group
numeric(0)
$names
[1] "male" "female"
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_well_to_dead2 1 well 4 dead2
5: 5 prob_disabled_to_disabled 2 disabled 2 disabled
6: 6 prob_disabled_to_dead 2 disabled 3 dead
7: 7 prob_disabled_to_dead2 2 disabled 4 dead2
8: 8 prob_dead_to_dead 3 dead 3 dead
9: 9 prob_dead_to_dead2 3 dead 4 dead2
10: 10 prob_dead2_to_dead2 4 dead2 4 dead2
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_well_to_well 1 well 1 well
2: 2 prob_well_to_disabled 1 well 2 disabled
3: 3 prob_well_to_dead 1 well 3 dead
4: 4 prob_disabled_to_disabled 2 disabled 2 disabled
5: 5 prob_disabled_to_dead 2 disabled 3 dead
6: 6 prob_dead_to_dead 3 dead 3 dead
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_B_to_B 2 B 2 B
5: 5 prob_B_to_C 2 B 3 C
6: 6 prob_C_to_C 3 C 3 C
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_B_to_B 2 B 2 B
5: 5 prob_B_to_C 2 B 3 C
6: 6 prob_C_to_C 3 C 3 C
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_B_to_B 2 B 2 B
5: 5 prob_B_to_C 2 B 3 C
6: 6 prob_C_to_C 3 C 3 C
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_A_to_D 1 A 4 D
5: 5 prob_B_to_B 2 B 2 B
6: 6 prob_B_to_C 2 B 3 C
7: 7 prob_B_to_D 2 B 4 D
8: 8 prob_C_to_C 3 C 3 C
9: 9 prob_C_to_D 3 C 4 D
10: 10 prob_D_to_D 4 D 4 D
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_B_to_B 2 B 2 B
5: 5 prob_B_to_C 2 B 3 C
6: 6 prob_C_to_C 3 C 3 C
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_B_to_B 2 B 2 B
5: 5 prob_B_to_C 2 B 3 C
6: 6 prob_C_to_C 3 C 3 C
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_B_to_B 2 B 2 B
5: 5 prob_B_to_C 2 B 3 C
6: 6 prob_C_to_C 3 C 3 C
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_A_to_A 1 A 1 A
2: 2 prob_A_to_B 1 A 2 B
3: 3 prob_A_to_C 1 A 3 C
4: 4 prob_B_to_B 2 B 2 B
5: 5 prob_B_to_C 2 B 3 C
6: 6 prob_C_to_C 3 C 3 C
[1] "The transition matrix as explained"
transition number probability name from from state to to state
1: 1 prob_Healthy_to_Healthy 1 Healthy 1 Healthy
2: 2 prob_Healthy_to_Dead 1 Healthy 2 Dead
3: 3 prob_Dead_to_Healthy 2 Dead 1 Healthy
4: 4 prob_Dead_to_Dead 2 Dead 2 Dead
[1] "For the distributions other than gamma,the code is not equipped to\n estimate the parameters"
[1] "For the distributions other than gamma,the code is not equipped to\n estimate the parameters"
Call:
lm(formula = admit ~ gre, data = dataset)
Residuals:
Min 1Q Median 3Q Max
-0.4755 -0.3415 -0.2522 0.5989 0.8966
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.1198407 0.1190510 -1.007 0.314722
gre 0.0007442 0.0001988 3.744 0.000208 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4587 on 398 degrees of freedom
Multiple R-squared: 0.03402, Adjusted R-squared: 0.03159
F-statistic: 14.02 on 1 and 398 DF, p-value: 0.0002081
ASSESSMENT OF THE LINEAR MODEL ASSUMPTIONS
USING THE GLOBAL TEST ON 4 DEGREES-OF-FREEDOM:
Level of Significance = 0.05
Call:
gvlma::gvlma(x = fit)
Value p-value Decision
Global Stat 65.312437 2.212e-13 Assumptions NOT satisfied!
Skewness 36.445627 1.570e-09 Assumptions NOT satisfied!
Kurtosis 28.227938 1.078e-07 Assumptions NOT satisfied!
Link Function 0.002174 9.628e-01 Assumptions acceptable.
Heteroscedasticity 0.636699 4.249e-01 Assumptions acceptable.
Call:
lm(formula = admit ~ gre, data = dataset)
Residuals:
Min 1Q Median 3Q Max
-0.4755 -0.3415 -0.2522 0.5989 0.8966
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.1198407 0.1190510 -1.007 0.314722
gre 0.0007442 0.0001988 3.744 0.000208 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4587 on 398 degrees of freedom
Multiple R-squared: 0.03402, Adjusted R-squared: 0.03159
F-statistic: 14.02 on 1 and 398 DF, p-value: 0.0002081
ASSESSMENT OF THE LINEAR MODEL ASSUMPTIONS
USING THE GLOBAL TEST ON 4 DEGREES-OF-FREEDOM:
Level of Significance = 0.05
Call:
gvlma::gvlma(x = fit)
Value p-value Decision
Global Stat 65.312437 2.212e-13 Assumptions NOT satisfied!
Skewness 36.445627 1.570e-09 Assumptions NOT satisfied!
Kurtosis 28.227938 1.078e-07 Assumptions NOT satisfied!
Link Function 0.002174 9.628e-01 Assumptions acceptable.
Heteroscedasticity 0.636699 4.249e-01 Assumptions acceptable.
Start: AIC=65.77
mpg ~ hp + wt + drat + disp
Df Sum of Sq RSS AIC
- disp 1 0.844 183.68 63.919
<none> 182.84 65.772
- drat 1 12.153 194.99 65.831
- hp 1 60.916 243.75 72.974
- wt 1 70.508 253.35 74.209
Step: AIC=63.92
mpg ~ hp + wt + drat
Df Sum of Sq RSS AIC
- drat 1 11.366 195.05 63.840
<none> 183.68 63.919
+ disp 1 0.844 182.84 65.772
- hp 1 85.559 269.24 74.156
- wt 1 107.771 291.45 76.693
Step: AIC=63.84
mpg ~ hp + wt
Df Sum of Sq RSS AIC
<none> 195.05 63.840
+ drat 1 11.366 183.68 63.919
+ disp 1 0.057 194.99 65.831
- hp 1 83.274 278.32 73.217
- wt 1 252.627 447.67 88.427
Call:
lm(formula = mpg ~ hp + wt + drat + disp, data = dataset)
Residuals:
Min 1Q Median 3Q Max
-3.5077 -1.9052 -0.5057 0.9821 5.6883
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 29.148738 6.293588 4.631 8.2e-05 ***
hp -0.034784 0.011597 -2.999 0.00576 **
wt -3.479668 1.078371 -3.227 0.00327 **
drat 1.768049 1.319779 1.340 0.19153
disp 0.003815 0.010805 0.353 0.72675
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.602 on 27 degrees of freedom
Multiple R-squared: 0.8376, Adjusted R-squared: 0.8136
F-statistic: 34.82 on 4 and 27 DF, p-value: 2.704e-10
ASSESSMENT OF THE LINEAR MODEL ASSUMPTIONS
USING THE GLOBAL TEST ON 4 DEGREES-OF-FREEDOM:
Level of Significance = 0.05
Call:
gvlma::gvlma(x = fit)
Value p-value Decision
Global Stat 13.93816 0.007495 Assumptions NOT satisfied!
Skewness 4.31310 0.037820 Assumptions NOT satisfied!
Kurtosis 0.01378 0.906542 Assumptions acceptable.
Link Function 8.71658 0.003153 Assumptions NOT satisfied!
Heteroscedasticity 0.89470 0.344207 Assumptions acceptable.
== Failed tests ================================================================
-- Failure (test-3a_trialdata_analysis_input_functions.R:154:3): testing get the coding values of a column in data --
ans$variable not equal to "arm".
'current' is not a factor
-- Failure (test-3a_trialdata_analysis_input_functions.R:155:3): testing get the coding values of a column in data --
ans$nonrescode not equal to "999".
'current' is not a factor
-- Failure (test-3a_trialdata_analysis_input_functions.R:161:3): testing get the coding values of a column in data --
ans$variable not equal to "arm".
'current' is not a factor
-- Error (test-3c_costing_medication_functions.R:1288:1): (code run outside of `test_that()`) --
Error: The used dosage is not in costing table
Backtrace:
x
1. \-packDAMipd::microcosting_liquids_wide(...) test-3c_costing_medication_functions.R:1288:0
-- Failure (test-4a_deterministic_sensitivity_analysis_functions.R:233:3): testing plotting deterministic sensitivity analysis --
the_plot$data$parameters not equal to c("cost_direct_med_B", "cost_comm_care_C").
'current' is not a factor
-- Failure (test-help_cost_analysis_functions.R:7:3): testing to get the subset of data compared to a string --
ans$brand not equal to "a".
'current' is not a factor
-- Failure (test-help_cost_analysis_functions.R:15:4): testing to get the subset of data compared to list of string --
ans$brand not equal to "a".
'current' is not a factor
-- Failure (test-help_cost_analysis_functions.R:24:3): testing to get the subset of data compared to list of string --
ans$xx not equal to c("bb", "aa").
'current' is not a factor
-- Failure (test-help_parameter_estimation_survival.R:94:3): testing creating a new dataset based on given one --
unique(new$check) not equal to "no".
'current' is not a factor
[ FAIL 9 | WARN 0 | SKIP 0 | PASS 994 ]
Error: Test failures
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64