Generate a design of presentation order based on Williams design.
prepare(n_panelist, product, blind_code = FALSE, seed = NULL)
| n_panelist | number of panelist |
|---|---|
| product | a numeric value of number or product or vector of product names |
| blind_code | wheteher to generate random three digit number for labeling |
| seed | an integer for anchoring randomisation |
a dataframe of sensory design with panelist column and order of product presentation columns
prepare(n_panelist = 30, product = letters[1:14], blind_code = FALSE)#> # Design of Experiment: <30 x 15> #> # Panelist: 30 subjects #> # Product: 14 items #> panelist order_1 order_2 order_3 order_4 order_5 order_6 order_7 order_8 #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 ind_001 n d c b g f j i #> 2 ind_002 d b n f c i g l #> 3 ind_003 b f d i n l c a #> 4 ind_004 f i b l d a n k #> 5 ind_005 i l f a b k d e #> 6 ind_006 l a i k f e b h #> 7 ind_007 a k l e i h f m #> 8 ind_008 k e a h l m i j #> 9 ind_009 e h k m a j l g #> 10 ind_010 h m e j k g a c #> # … with 20 more rows, and 6 more variables: order_9 <chr>, order_10 <chr>, #> # order_11 <chr>, order_12 <chr>, order_13 <chr>, order_14 <chr>prepare(n_panelist = 30, product = letters[1:14], blind_code = TRUE)#> # Design of Experiment: <30 x 15> #> # Panelist: 30 subjects #> # Product: 14 items #> panelist order_1 order_2 order_3 order_4 order_5 order_6 order_7 order_8 #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 ind_001 l (409) h (257) d (605) g (648) b (523) n (507) f (150) e (239) #> 2 ind_002 h (257) g (648) l (409) n (507) d (605) e (239) b (523) c (728) #> 3 ind_003 g (648) n (507) h (257) e (239) l (409) c (728) d (605) a (371) #> 4 ind_004 n (507) e (239) g (648) c (728) h (257) a (371) l (409) m (835) #> 5 ind_005 e (239) c (728) n (507) a (371) g (648) m (835) h (257) i (399) #> 6 ind_006 c (728) a (371) e (239) m (835) n (507) i (399) g (648) k (918) #> 7 ind_007 a (371) m (835) c (728) i (399) e (239) k (918) n (507) j (147) #> 8 ind_008 m (835) i (399) a (371) k (918) c (728) j (147) e (239) f (150) #> 9 ind_009 i (399) k (918) m (835) j (147) a (371) f (150) c (728) b (523) #> 10 ind_010 k (918) j (147) i (399) f (150) m (835) b (523) a (371) d (605) #> # … with 20 more rows, and 6 more variables: order_9 <chr>, order_10 <chr>, #> # order_11 <chr>, order_12 <chr>, order_13 <chr>, order_14 <chr>design <- prepare(n_panelist = 20, product = 5, blind_code = TRUE) design#> # Design of Experiment: <20 x 6> #> # Panelist: 20 subjects #> # Product: 5 items #> panelist order_1 order_2 order_3 order_4 order_5 #> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 ind_001 prod_02 (517) prod_04 (519) prod_01 (555) prod_03 (430) prod_05 (44… #> 2 ind_002 prod_04 (519) prod_03 (430) prod_02 (517) prod_05 (448) prod_01 (55… #> 3 ind_003 prod_03 (430) prod_05 (448) prod_04 (519) prod_01 (555) prod_02 (51… #> 4 ind_004 prod_05 (448) prod_01 (555) prod_03 (430) prod_02 (517) prod_04 (51… #> 5 ind_005 prod_01 (555) prod_02 (517) prod_05 (448) prod_04 (519) prod_03 (43… #> 6 ind_006 prod_05 (448) prod_03 (430) prod_01 (555) prod_04 (519) prod_02 (51… #> 7 ind_007 prod_01 (555) prod_05 (448) prod_02 (517) prod_03 (430) prod_04 (51… #> 8 ind_008 prod_02 (517) prod_01 (555) prod_04 (519) prod_05 (448) prod_03 (43… #> 9 ind_009 prod_04 (519) prod_02 (517) prod_03 (430) prod_01 (555) prod_05 (44… #> 10 ind_010 prod_03 (430) prod_04 (519) prod_05 (448) prod_02 (517) prod_01 (55… #> 11 ind_011 prod_02 (517) prod_04 (519) prod_01 (555) prod_03 (430) prod_05 (44… #> 12 ind_012 prod_04 (519) prod_03 (430) prod_02 (517) prod_05 (448) prod_01 (55… #> 13 ind_013 prod_03 (430) prod_05 (448) prod_04 (519) prod_01 (555) prod_02 (51… #> 14 ind_014 prod_05 (448) prod_01 (555) prod_03 (430) prod_02 (517) prod_04 (51… #> 15 ind_015 prod_01 (555) prod_02 (517) prod_05 (448) prod_04 (519) prod_03 (43… #> 16 ind_016 prod_05 (448) prod_03 (430) prod_01 (555) prod_04 (519) prod_02 (51… #> 17 ind_017 prod_01 (555) prod_05 (448) prod_02 (517) prod_03 (430) prod_04 (51… #> 18 ind_018 prod_02 (517) prod_01 (555) prod_04 (519) prod_05 (448) prod_03 (43… #> 19 ind_019 prod_04 (519) prod_02 (517) prod_03 (430) prod_01 (555) prod_05 (44… #> 20 ind_020 prod_03 (430) prod_04 (519) prod_05 (448) prod_02 (517) prod_01 (55…