R/extensions.R, R/summary_functions.R
summary-methods.RdExtension of summary() for objects in TestDesign package
# S4 method for class 'item_pool'
summary(object)
# S4 method for class 'item_attrib'
summary(object)
# S4 method for class 'st_attrib'
summary(object)
# S4 method for class 'constraints'
summary(object)
# S4 method for class 'output_Static'
summary(object, simple = FALSE)
# S4 method for class 'output_Shadow_all'
summary(object, simple = FALSE)summary(itempool_science)
#> Item pool
#> # of items : 1000
#> item_3PL : 918
#> item_GPC : 82
#> has SE : FALSE
summary(itemattrib_science)
#> Item attributes
#> # of attributes : 9
#> INDEX : (1000 levels)
#> ID : (1000 levels)
#> LEVEL : 3 4 5
#> STANDARD : 1 2 3 4
#> OBJECTIVE : (28 levels)
#> DOK : 1 2 3
#> TYPE : DRAG EQTN FILL GRAPH HOTS MATCH SRMU SRSI
#> PVALUE : (1000 levels)
#> PTBIS : (1000 levels)
cfg <- createStaticTestConfig()
solution <- Static(cfg, constraints_science)
summary(solution)
#> Static assembly
#>
#> # of targets: 3
#> type of objective: MaxInfo
#> # of selected items: 30
#>
#> theta info score
#> -1.2 11.225 10.376
#> 0.0 19.166 24.741
#> 1.2 10.995 38.875
#>
#> CONSTRAINT_ID TYPE WHAT CONDITION LB UB
#> C1 NUMBER ITEM 30 30
#> C2 NUMBER ITEM LEVEL == 3 10 10
#> C3 NUMBER ITEM LEVEL == 4 10 10
#> C4 NUMBER ITEM LEVEL == 5 10 10
#> C5 NUMBER ITEM STANDARD == 1 17 20
#> C6 NUMBER ITEM STANDARD %in% c(2, 4) 6 8
#> C7 NUMBER ITEM STANDARD == 3 2 4
#> C8 NUMBER ITEM OBJECTIVE == "1A" 2 3
#> C9 NUMBER ITEM OBJECTIVE %in% c("1B", "1C", "1I", "1G") 5 6
#> C10 NUMBER ITEM OBJECTIVE %in% c("1D", "1F") 5 6
#> C11 NUMBER ITEM OBJECTIVE %in% c("1E", "1J", "1K") 3 4
#> C12 NUMBER ITEM OBJECTIVE == "1H" 1 1
#> C13 NUMBER ITEM OBJECTIVE == "2A" 2 2
#> C14 NUMBER ITEM OBJECTIVE %in% c("2B", "2C", "2D") 1 1
#> C15 NUMBER ITEM OBJECTIVE %in% c("4A", "4D") 1 1
#> C16 NUMBER ITEM OBJECTIVE %in% c("4B", "4E") 1 1
#> C17 NUMBER ITEM OBJECTIVE %in% c("4C", "4F") 1 1
#> C18 NUMBER ITEM OBJECTIVE %in% c("3A", "3D") 3 3
#> C19 NUMBER ITEM OBJECTIVE %in% c("3B", "3E") 2 3
#> C20 NUMBER ITEM OBJECTIVE %in% c("3C", "3F") 0 3
#> C21 NUMBER ITEM STANDARD == 1 & DOK >= 2 7 30
#> C22 NUMBER ITEM STANDARD %in% c(2, 4) & DOK >= 3 2 30
#> C23 NUMBER ITEM STANDARD == 3 & DOK >= 3 2 30
#> C24 NUMBER ITEM TYPE == "DRAG" 2 4
#> C25 NUMBER ITEM TYPE == "EQTN" 12 15
#> C26 NUMBER ITEM TYPE == "FILL" 1 2
#> C27 NUMBER ITEM TYPE == "GRAPH" 1 3
#> C28 NUMBER ITEM TYPE == "HOTS" 1 3
#> C29 NUMBER ITEM TYPE == "MATCH" 2 4
#> C30 NUMBER ITEM TYPE == "SRMU" 1 2
#> C31 NUMBER ITEM TYPE == "SRSI" 5 8
#> C32 ORDER ITEM LEVEL
#> C33 ENEMY ITEM ID %in% c("SC00001", "SC00002")
#> C34 INCLUDE ITEM ID %in% c("SC00003", "SC00004")
#> C35 EXCLUDE ITEM PTBIS < 0.15
#> C36 ALLORNONE ITEM ID %in% c("SC00005", "SC00006")
#> ONOFF COUNT solution
#> 1000 30
#> 342 10
#> 335 10
#> 323 10
#> 689 19
#> 141 7
#> 170 4
#> 83 3
#> 196 6
#> 228 5
#> 141 4
#> 30 1
#> 20 2
#> 34 1
#> 39 1
#> 21 1
#> 25 1
#> 64 3
#> 64 2
#> 43 0
#> 381 13
#> 42 3
#> 97 2
#> 70 2
#> 449 15
#> 21 1
#> 34 1
#> 72 3
#> 117 2
#> 32 1
#> 205 5
#>
#> 2 0
#> 2 2
#> 18 0
#> 2 0
summary(solution, simple = TRUE)
#> Static assembly
#>
#> # of targets: 3
#> type of objective: MaxInfo
#> # of selected items: 30
#>
#> theta info score
#> -1.2 11.225 10.376
#> 0.0 19.166 24.741
#> 1.2 10.995 38.875
cfg <- createShadowTestConfig()
solution <- Shadow(cfg, constraints_science, true_theta = seq(-1, 1, 1))
summary(solution)
#> Shadow assembly
#>
#> # of simulees : 3
#> test length : 30
#>
#> theta estimation statistics
#> MSE : 0.015141
#> bias : -0.065749
#> Average SE : 0.237613
#> corr : 0.995142
#>
#> adaptivity indices
#> corr : 0.996862
#> SD ratio : 0.548760
#> PRV : 0.652788
#> info : 0.653061
#>
#> CONSTRAINT_ID TYPE WHAT CONDITION LB UB
#> C1 NUMBER ITEM 30 30
#> C2 NUMBER ITEM LEVEL == 3 10 10
#> C3 NUMBER ITEM LEVEL == 4 10 10
#> C4 NUMBER ITEM LEVEL == 5 10 10
#> C5 NUMBER ITEM STANDARD == 1 17 20
#> C6 NUMBER ITEM STANDARD %in% c(2, 4) 6 8
#> C7 NUMBER ITEM STANDARD == 3 2 4
#> C8 NUMBER ITEM OBJECTIVE == "1A" 2 3
#> C9 NUMBER ITEM OBJECTIVE %in% c("1B", "1C", "1I", "1G") 5 6
#> C10 NUMBER ITEM OBJECTIVE %in% c("1D", "1F") 5 6
#> C11 NUMBER ITEM OBJECTIVE %in% c("1E", "1J", "1K") 3 4
#> C12 NUMBER ITEM OBJECTIVE == "1H" 1 1
#> C13 NUMBER ITEM OBJECTIVE == "2A" 2 2
#> C14 NUMBER ITEM OBJECTIVE %in% c("2B", "2C", "2D") 1 1
#> C15 NUMBER ITEM OBJECTIVE %in% c("4A", "4D") 1 1
#> C16 NUMBER ITEM OBJECTIVE %in% c("4B", "4E") 1 1
#> C17 NUMBER ITEM OBJECTIVE %in% c("4C", "4F") 1 1
#> C18 NUMBER ITEM OBJECTIVE %in% c("3A", "3D") 3 3
#> C19 NUMBER ITEM OBJECTIVE %in% c("3B", "3E") 2 3
#> C20 NUMBER ITEM OBJECTIVE %in% c("3C", "3F") 0 3
#> C21 NUMBER ITEM STANDARD == 1 & DOK >= 2 7 30
#> C22 NUMBER ITEM STANDARD %in% c(2, 4) & DOK >= 3 2 30
#> C23 NUMBER ITEM STANDARD == 3 & DOK >= 3 2 30
#> C24 NUMBER ITEM TYPE == "DRAG" 2 4
#> C25 NUMBER ITEM TYPE == "EQTN" 12 15
#> C26 NUMBER ITEM TYPE == "FILL" 1 2
#> C27 NUMBER ITEM TYPE == "GRAPH" 1 3
#> C28 NUMBER ITEM TYPE == "HOTS" 1 3
#> C29 NUMBER ITEM TYPE == "MATCH" 2 4
#> C30 NUMBER ITEM TYPE == "SRMU" 1 2
#> C31 NUMBER ITEM TYPE == "SRSI" 5 8
#> C32 ORDER ITEM LEVEL
#> C33 ENEMY ITEM ID %in% c("SC00001", "SC00002")
#> C34 INCLUDE ITEM ID %in% c("SC00003", "SC00004")
#> C35 EXCLUDE ITEM PTBIS < 0.15
#> C36 ALLORNONE ITEM ID %in% c("SC00005", "SC00006")
#> ONOFF COUNT mean sd min max
#> 1000 30 0 30 30
#> 342 10 0 10 10
#> 335 10 0 10 10
#> 323 10 0 10 10
#> 689 19 0 19 19
#> 141 7 0 7 7
#> 170 4 0 4 4
#> 83 2.667 0.577 2 3
#> 196 6 0 6 6
#> 228 5.333 0.577 5 6
#> 141 4 0 4 4
#> 30 1 0 1 1
#> 20 2 0 2 2
#> 34 1 0 1 1
#> 39 1 0 1 1
#> 21 1 0 1 1
#> 25 1 0 1 1
#> 64 3 0 3 3
#> 64 2 0 2 2
#> 43 0 0 0 0
#> 381 12.333 0.577 12 13
#> 42 2.667 0.577 2 3
#> 97 2.333 0.577 2 3
#> 70 2.667 1.155 2 4
#> 449 14.333 1.155 13 15
#> 21 1 0 1 1
#> 34 1 0 1 1
#> 72 3 0 3 3
#> 117 2 0 2 2
#> 32 1 0 1 1
#> 205 5 0 5 5
#>
#> 2 0 0 0 0
#> 2 2 0 2 2
#> 18 0 0 0 0
#> 2 0 0 0 0
summary(solution, simple = TRUE)
#> Shadow assembly
#>
#> # of simulees : 3
#> test length : 30
#>
#> theta estimation statistics
#> MSE : 0.015141
#> bias : -0.065749
#> Average SE : 0.237613
#> corr : 0.995142
#>
#> adaptivity indices
#> corr : 0.996862
#> SD ratio : 0.548760
#> PRV : 0.652788
#> info : 0.653061
#>