Closed szimmer closed 11 months ago
This addresses #162
It also removes some odd //n characters that are in the replicate weights. I cannot figure out where these are added in the code so I hack it to remove them before printing. There's probably a better solution.
Some examples below but no formal tests:
# devtools::install_github("https://github.com/szimmer/srvyr/tree/print-summary-width") library(tidyverse) library(tidycensus) library(srvyr) #> #> Attaching package: 'srvyr' #> The following object is masked from 'package:stats': #> #> filter pums_in <- get_pums( variables = c("NP", "BDSP", "HINCP"), state = "37", puma = c("01301", "01302"), rep_weights = "housing", year = 2020, survey = "acs5", variables_filter = list(SPORDER = 1, TYPEHUGQ = 1) ) #> Getting data from the 2016-2020 5-year ACS Public Use Microdata Sample des_acs <- pums_in %>% as_survey_rep( weights = WGTP, repweights = num_range("WGTP", 1:80), type = "JK1", mse = TRUE, scale = 4 / 80 ) options(width=120) des_acs #> Call: Called via srvyr #> Unstratified cluster jacknife (JK1) with 80 replicates and MSE variances. #> Sampling variables: #> - repweights: `WGTP1 + WGTP2 + WGTP3 + WGTP4 + WGTP5 + WGTP6 + WGTP7 + WGTP8 + WGTP9 + WGTP10 + WGTP11 + WGTP12 + #> WGTP13 + WGTP14 + WGTP15 + WGTP16 + WGTP17 + WGTP18 + WGTP19 + WGTP20 + WGTP21 + WGTP22 + WGTP23 + WGTP24 + WGTP25 #> + WGTP26 + WGTP27 + WGTP28 + WGTP29 + WGTP30 + WGTP31 + WGTP32 + WGTP33 + WGTP34 + WGTP35 + WGTP36 + WGTP37 + #> WGTP38 + WGTP39 + WGTP40 + WGTP41 + WGTP42 + WGTP43 + WGTP44 + WGTP45 + WGTP46 + WGTP47 + WGTP48 + WGTP49 + WGTP50 #> + WGTP51 + WGTP52 + WGTP53 + WGTP54 + WGTP55 + WGTP56 + WGTP57 + WGTP58 + WGTP59 + WGTP60 + WGTP61 + WGTP62 + #> WGTP63 + WGTP64 + WGTP65 + WGTP66 + WGTP67 + WGTP68 + WGTP69 + WGTP70 + WGTP71 + WGTP72 + WGTP73 + WGTP74 + WGTP75 #> + WGTP76 + WGTP77 + WGTP78 + WGTP79 + WGTP80` #> - weights: WGTP #> Data variables: #> - SERIALNO (chr), SPORDER (dbl), NP (dbl), BDSP (dbl), HINCP (dbl), PUMA (chr), ST (chr), TYPEHUGQ (chr), WGTP (dbl), #> PWGTP (dbl), WGTP1 (dbl), WGTP2 (dbl), WGTP3 (dbl), WGTP4 (dbl), WGTP5 (dbl), WGTP6 (dbl), WGTP7 (dbl), WGTP8 #> (dbl), WGTP9 (dbl), WGTP10 (dbl), WGTP11 (dbl), WGTP12 (dbl), WGTP13 (dbl), WGTP14 (dbl), WGTP15 (dbl), WGTP16 #> (dbl), WGTP17 (dbl), WGTP18 (dbl), WGTP19 (dbl), WGTP20 (dbl), WGTP21 (dbl), WGTP22 (dbl), WGTP23 (dbl), WGTP24 #> (dbl), WGTP25 (dbl), WGTP26 (dbl), WGTP27 (dbl), WGTP28 (dbl), WGTP29 (dbl), WGTP30 (dbl), WGTP31 (dbl), WGTP32 #> (dbl), WGTP33 (dbl), WGTP34 (dbl), WGTP35 (dbl), WGTP36 (dbl), WGTP37 (dbl), WGTP38 (dbl), WGTP39 (dbl), WGTP40 #> (dbl), WGTP41 (dbl), WGTP42 (dbl), WGTP43 (dbl), WGTP44 (dbl), WGTP45 (dbl), WGTP46 (dbl), WGTP47 (dbl), WGTP48 #> (dbl), WGTP49 (dbl), WGTP50 (dbl), WGTP51 (dbl), WGTP52 (dbl), WGTP53 (dbl), WGTP54 (dbl), WGTP55 (dbl), WGTP56 #> (dbl), WGTP57 (dbl), WGTP58 (dbl), WGTP59 (dbl), WGTP60 (dbl), WGTP61 (dbl), WGTP62 (dbl), WGTP63 (dbl), WGTP64 #> (dbl), WGTP65 (dbl), WGTP66 (dbl), WGTP67 (dbl), WGTP68 (dbl), WGTP69 (dbl), WGTP70 (dbl), WGTP71 (dbl), WGTP72 #> (dbl), WGTP73 (dbl), WGTP74 (dbl), WGTP75 (dbl), WGTP76 (dbl), WGTP77 (dbl), WGTP78 (dbl), WGTP79 (dbl), WGTP80 #> (dbl) summary(des_acs) #> Call: Called via srvyr #> Unstratified cluster jacknife (JK1) with 80 replicates and MSE variances. #> Sampling variables: #> - repweights: `WGTP1 + WGTP2 + WGTP3 + WGTP4 + WGTP5 + WGTP6 + WGTP7 + WGTP8 + WGTP9 + WGTP10 + WGTP11 + WGTP12 + #> WGTP13 + WGTP14 + WGTP15 + WGTP16 + WGTP17 + WGTP18 + WGTP19 + WGTP20 + WGTP21 + WGTP22 + WGTP23 + WGTP24 + WGTP25 #> + WGTP26 + WGTP27 + WGTP28 + WGTP29 + WGTP30 + WGTP31 + WGTP32 + WGTP33 + WGTP34 + WGTP35 + WGTP36 + WGTP37 + #> WGTP38 + WGTP39 + WGTP40 + WGTP41 + WGTP42 + WGTP43 + WGTP44 + WGTP45 + WGTP46 + WGTP47 + WGTP48 + WGTP49 + WGTP50 #> + WGTP51 + WGTP52 + WGTP53 + WGTP54 + WGTP55 + WGTP56 + WGTP57 + WGTP58 + WGTP59 + WGTP60 + WGTP61 + WGTP62 + #> WGTP63 + WGTP64 + WGTP65 + WGTP66 + WGTP67 + WGTP68 + WGTP69 + WGTP70 + WGTP71 + WGTP72 + WGTP73 + WGTP74 + WGTP75 #> + WGTP76 + WGTP77 + WGTP78 + WGTP79 + WGTP80` #> - weights: WGTP #> Data variables: #> - SERIALNO (chr), SPORDER (dbl), NP (dbl), BDSP (dbl), HINCP (dbl), PUMA (chr), ST (chr), TYPEHUGQ (chr), WGTP (dbl), #> PWGTP (dbl), WGTP1 (dbl), WGTP2 (dbl), WGTP3 (dbl), WGTP4 (dbl), WGTP5 (dbl), WGTP6 (dbl), WGTP7 (dbl), WGTP8 #> (dbl), WGTP9 (dbl), WGTP10 (dbl), WGTP11 (dbl), WGTP12 (dbl), WGTP13 (dbl), WGTP14 (dbl), WGTP15 (dbl), WGTP16 #> (dbl), WGTP17 (dbl), WGTP18 (dbl), WGTP19 (dbl), WGTP20 (dbl), WGTP21 (dbl), WGTP22 (dbl), WGTP23 (dbl), WGTP24 #> (dbl), WGTP25 (dbl), WGTP26 (dbl), WGTP27 (dbl), WGTP28 (dbl), WGTP29 (dbl), WGTP30 (dbl), WGTP31 (dbl), WGTP32 #> (dbl), WGTP33 (dbl), WGTP34 (dbl), WGTP35 (dbl), WGTP36 (dbl), WGTP37 (dbl), WGTP38 (dbl), WGTP39 (dbl), WGTP40 #> (dbl), WGTP41 (dbl), WGTP42 (dbl), WGTP43 (dbl), WGTP44 (dbl), WGTP45 (dbl), WGTP46 (dbl), WGTP47 (dbl), WGTP48 #> (dbl), WGTP49 (dbl), WGTP50 (dbl), WGTP51 (dbl), WGTP52 (dbl), WGTP53 (dbl), WGTP54 (dbl), WGTP55 (dbl), WGTP56 #> (dbl), WGTP57 (dbl), WGTP58 (dbl), WGTP59 (dbl), WGTP60 (dbl), WGTP61 (dbl), WGTP62 (dbl), WGTP63 (dbl), WGTP64 #> (dbl), WGTP65 (dbl), WGTP66 (dbl), WGTP67 (dbl), WGTP68 (dbl), WGTP69 (dbl), WGTP70 (dbl), WGTP71 (dbl), WGTP72 #> (dbl), WGTP73 (dbl), WGTP74 (dbl), WGTP75 (dbl), WGTP76 (dbl), WGTP77 (dbl), WGTP78 (dbl), WGTP79 (dbl), WGTP80 #> (dbl) #> Variables: #> [1] "SERIALNO" "SPORDER" "NP" "BDSP" "HINCP" "PUMA" "ST" "TYPEHUGQ" "WGTP" "PWGTP" #> [11] "WGTP1" "WGTP2" "WGTP3" "WGTP4" "WGTP5" "WGTP6" "WGTP7" "WGTP8" "WGTP9" "WGTP10" #> [21] "WGTP11" "WGTP12" "WGTP13" "WGTP14" "WGTP15" "WGTP16" "WGTP17" "WGTP18" "WGTP19" "WGTP20" #> [31] "WGTP21" "WGTP22" "WGTP23" "WGTP24" "WGTP25" "WGTP26" "WGTP27" "WGTP28" "WGTP29" "WGTP30" #> [41] "WGTP31" "WGTP32" "WGTP33" "WGTP34" "WGTP35" "WGTP36" "WGTP37" "WGTP38" "WGTP39" "WGTP40" #> [51] "WGTP41" "WGTP42" "WGTP43" "WGTP44" "WGTP45" "WGTP46" "WGTP47" "WGTP48" "WGTP49" "WGTP50" #> [61] "WGTP51" "WGTP52" "WGTP53" "WGTP54" "WGTP55" "WGTP56" "WGTP57" "WGTP58" "WGTP59" "WGTP60" #> [71] "WGTP61" "WGTP62" "WGTP63" "WGTP64" "WGTP65" "WGTP66" "WGTP67" "WGTP68" "WGTP69" "WGTP70" #> [81] "WGTP71" "WGTP72" "WGTP73" "WGTP74" "WGTP75" "WGTP76" "WGTP77" "WGTP78" "WGTP79" "WGTP80" options(width=60) des_acs #> Call: Called via srvyr #> Unstratified cluster jacknife (JK1) with 80 replicates and MSE variances. #> Sampling variables: #> - repweights: `WGTP1 + WGTP2 + WGTP3 + WGTP4 + WGTP5 + #> WGTP6 + WGTP7 + WGTP8 + WGTP9 + WGTP10 + WGTP11 + #> WGTP12 + WGTP13 + WGTP14 + WGTP15 + WGTP16 + WGTP17 + #> WGTP18 + WGTP19 + WGTP20 + WGTP21 + WGTP22 + WGTP23 + #> WGTP24 + WGTP25 + WGTP26 + WGTP27 + WGTP28 + WGTP29 + #> WGTP30 + WGTP31 + WGTP32 + WGTP33 + WGTP34 + WGTP35 + #> WGTP36 + WGTP37 + WGTP38 + WGTP39 + WGTP40 + WGTP41 + #> WGTP42 + WGTP43 + WGTP44 + WGTP45 + WGTP46 + WGTP47 + #> WGTP48 + WGTP49 + WGTP50 + WGTP51 + WGTP52 + WGTP53 + #> WGTP54 + WGTP55 + WGTP56 + WGTP57 + WGTP58 + WGTP59 + #> WGTP60 + WGTP61 + WGTP62 + WGTP63 + WGTP64 + WGTP65 + #> WGTP66 + WGTP67 + WGTP68 + WGTP69 + WGTP70 + WGTP71 + #> WGTP72 + WGTP73 + WGTP74 + WGTP75 + WGTP76 + WGTP77 + #> WGTP78 + WGTP79 + WGTP80` #> - weights: WGTP #> Data variables: #> - SERIALNO (chr), SPORDER (dbl), NP (dbl), BDSP (dbl), #> HINCP (dbl), PUMA (chr), ST (chr), TYPEHUGQ (chr), WGTP #> (dbl), PWGTP (dbl), WGTP1 (dbl), WGTP2 (dbl), WGTP3 #> (dbl), WGTP4 (dbl), WGTP5 (dbl), WGTP6 (dbl), WGTP7 #> (dbl), WGTP8 (dbl), WGTP9 (dbl), WGTP10 (dbl), WGTP11 #> (dbl), WGTP12 (dbl), WGTP13 (dbl), WGTP14 (dbl), WGTP15 #> (dbl), WGTP16 (dbl), WGTP17 (dbl), WGTP18 (dbl), WGTP19 #> (dbl), WGTP20 (dbl), WGTP21 (dbl), WGTP22 (dbl), WGTP23 #> (dbl), WGTP24 (dbl), WGTP25 (dbl), WGTP26 (dbl), WGTP27 #> (dbl), WGTP28 (dbl), WGTP29 (dbl), WGTP30 (dbl), WGTP31 #> (dbl), WGTP32 (dbl), WGTP33 (dbl), WGTP34 (dbl), WGTP35 #> (dbl), WGTP36 (dbl), WGTP37 (dbl), WGTP38 (dbl), WGTP39 #> (dbl), WGTP40 (dbl), WGTP41 (dbl), WGTP42 (dbl), WGTP43 #> (dbl), WGTP44 (dbl), WGTP45 (dbl), WGTP46 (dbl), WGTP47 #> (dbl), WGTP48 (dbl), WGTP49 (dbl), WGTP50 (dbl), WGTP51 #> (dbl), WGTP52 (dbl), WGTP53 (dbl), WGTP54 (dbl), WGTP55 #> (dbl), WGTP56 (dbl), WGTP57 (dbl), WGTP58 (dbl), WGTP59 #> (dbl), WGTP60 (dbl), WGTP61 (dbl), WGTP62 (dbl), WGTP63 #> (dbl), WGTP64 (dbl), WGTP65 (dbl), WGTP66 (dbl), WGTP67 #> (dbl), WGTP68 (dbl), WGTP69 (dbl), WGTP70 (dbl), WGTP71 #> (dbl), WGTP72 (dbl), WGTP73 (dbl), WGTP74 (dbl), WGTP75 #> (dbl), WGTP76 (dbl), WGTP77 (dbl), WGTP78 (dbl), WGTP79 #> (dbl), WGTP80 (dbl) summary(des_acs) #> Call: Called via srvyr #> Unstratified cluster jacknife (JK1) with 80 replicates and MSE variances. #> Sampling variables: #> - repweights: `WGTP1 + WGTP2 + WGTP3 + WGTP4 + WGTP5 + #> WGTP6 + WGTP7 + WGTP8 + WGTP9 + WGTP10 + WGTP11 + #> WGTP12 + WGTP13 + WGTP14 + WGTP15 + WGTP16 + WGTP17 + #> WGTP18 + WGTP19 + WGTP20 + WGTP21 + WGTP22 + WGTP23 + #> WGTP24 + WGTP25 + WGTP26 + WGTP27 + WGTP28 + WGTP29 + #> WGTP30 + WGTP31 + WGTP32 + WGTP33 + WGTP34 + WGTP35 + #> WGTP36 + WGTP37 + WGTP38 + WGTP39 + WGTP40 + WGTP41 + #> WGTP42 + WGTP43 + WGTP44 + WGTP45 + WGTP46 + WGTP47 + #> WGTP48 + WGTP49 + WGTP50 + WGTP51 + WGTP52 + WGTP53 + #> WGTP54 + WGTP55 + WGTP56 + WGTP57 + WGTP58 + WGTP59 + #> WGTP60 + WGTP61 + WGTP62 + WGTP63 + WGTP64 + WGTP65 + #> WGTP66 + WGTP67 + WGTP68 + WGTP69 + WGTP70 + WGTP71 + #> WGTP72 + WGTP73 + WGTP74 + WGTP75 + WGTP76 + WGTP77 + #> WGTP78 + WGTP79 + WGTP80` #> - weights: WGTP #> Data variables: #> - SERIALNO (chr), SPORDER (dbl), NP (dbl), BDSP (dbl), #> HINCP (dbl), PUMA (chr), ST (chr), TYPEHUGQ (chr), WGTP #> (dbl), PWGTP (dbl), WGTP1 (dbl), WGTP2 (dbl), WGTP3 #> (dbl), WGTP4 (dbl), WGTP5 (dbl), WGTP6 (dbl), WGTP7 #> (dbl), WGTP8 (dbl), WGTP9 (dbl), WGTP10 (dbl), WGTP11 #> (dbl), WGTP12 (dbl), WGTP13 (dbl), WGTP14 (dbl), WGTP15 #> (dbl), WGTP16 (dbl), WGTP17 (dbl), WGTP18 (dbl), WGTP19 #> (dbl), WGTP20 (dbl), WGTP21 (dbl), WGTP22 (dbl), WGTP23 #> (dbl), WGTP24 (dbl), WGTP25 (dbl), WGTP26 (dbl), WGTP27 #> (dbl), WGTP28 (dbl), WGTP29 (dbl), WGTP30 (dbl), WGTP31 #> (dbl), WGTP32 (dbl), WGTP33 (dbl), WGTP34 (dbl), WGTP35 #> (dbl), WGTP36 (dbl), WGTP37 (dbl), WGTP38 (dbl), WGTP39 #> (dbl), WGTP40 (dbl), WGTP41 (dbl), WGTP42 (dbl), WGTP43 #> (dbl), WGTP44 (dbl), WGTP45 (dbl), WGTP46 (dbl), WGTP47 #> (dbl), WGTP48 (dbl), WGTP49 (dbl), WGTP50 (dbl), WGTP51 #> (dbl), WGTP52 (dbl), WGTP53 (dbl), WGTP54 (dbl), WGTP55 #> (dbl), WGTP56 (dbl), WGTP57 (dbl), WGTP58 (dbl), WGTP59 #> (dbl), WGTP60 (dbl), WGTP61 (dbl), WGTP62 (dbl), WGTP63 #> (dbl), WGTP64 (dbl), WGTP65 (dbl), WGTP66 (dbl), WGTP67 #> (dbl), WGTP68 (dbl), WGTP69 (dbl), WGTP70 (dbl), WGTP71 #> (dbl), WGTP72 (dbl), WGTP73 (dbl), WGTP74 (dbl), WGTP75 #> (dbl), WGTP76 (dbl), WGTP77 (dbl), WGTP78 (dbl), WGTP79 #> (dbl), WGTP80 (dbl) #> Variables: #> [1] "SERIALNO" "SPORDER" "NP" "BDSP" "HINCP" #> [6] "PUMA" "ST" "TYPEHUGQ" "WGTP" "PWGTP" #> [11] "WGTP1" "WGTP2" "WGTP3" "WGTP4" "WGTP5" #> [16] "WGTP6" "WGTP7" "WGTP8" "WGTP9" "WGTP10" #> [21] "WGTP11" "WGTP12" "WGTP13" "WGTP14" "WGTP15" #> [26] "WGTP16" "WGTP17" "WGTP18" "WGTP19" "WGTP20" #> [31] "WGTP21" "WGTP22" "WGTP23" "WGTP24" "WGTP25" #> [36] "WGTP26" "WGTP27" "WGTP28" "WGTP29" "WGTP30" #> [41] "WGTP31" "WGTP32" "WGTP33" "WGTP34" "WGTP35" #> [46] "WGTP36" "WGTP37" "WGTP38" "WGTP39" "WGTP40" #> [51] "WGTP41" "WGTP42" "WGTP43" "WGTP44" "WGTP45" #> [56] "WGTP46" "WGTP47" "WGTP48" "WGTP49" "WGTP50" #> [61] "WGTP51" "WGTP52" "WGTP53" "WGTP54" "WGTP55" #> [66] "WGTP56" "WGTP57" "WGTP58" "WGTP59" "WGTP60" #> [71] "WGTP61" "WGTP62" "WGTP63" "WGTP64" "WGTP65" #> [76] "WGTP66" "WGTP67" "WGTP68" "WGTP69" "WGTP70" #> [81] "WGTP71" "WGTP72" "WGTP73" "WGTP74" "WGTP75" #> [86] "WGTP76" "WGTP77" "WGTP78" "WGTP79" "WGTP80" # Looking at grouping variables des_acs %>% group_by(BDSP) #> Call: Called via srvyr #> Unstratified cluster jacknife (JK1) with 80 replicates and MSE variances. #> Sampling variables: #> - repweights: `WGTP1 + WGTP2 + WGTP3 + WGTP4 + WGTP5 + #> WGTP6 + WGTP7 + WGTP8 + WGTP9 + WGTP10 + WGTP11 + #> WGTP12 + WGTP13 + WGTP14 + WGTP15 + WGTP16 + WGTP17 + #> WGTP18 + WGTP19 + WGTP20 + WGTP21 + WGTP22 + WGTP23 + #> WGTP24 + WGTP25 + WGTP26 + WGTP27 + WGTP28 + WGTP29 + #> WGTP30 + WGTP31 + WGTP32 + WGTP33 + WGTP34 + WGTP35 + #> WGTP36 + WGTP37 + WGTP38 + WGTP39 + WGTP40 + WGTP41 + #> WGTP42 + WGTP43 + WGTP44 + WGTP45 + WGTP46 + WGTP47 + #> WGTP48 + WGTP49 + WGTP50 + WGTP51 + WGTP52 + WGTP53 + #> WGTP54 + WGTP55 + WGTP56 + WGTP57 + WGTP58 + WGTP59 + #> WGTP60 + WGTP61 + WGTP62 + WGTP63 + WGTP64 + WGTP65 + #> WGTP66 + WGTP67 + WGTP68 + WGTP69 + WGTP70 + WGTP71 + #> WGTP72 + WGTP73 + WGTP74 + WGTP75 + WGTP76 + WGTP77 + #> WGTP78 + WGTP79 + WGTP80` #> - weights: WGTP #> Grouping variables: #> - BDSP #> Data variables: #> - SERIALNO (chr), SPORDER (dbl), NP (dbl), BDSP (dbl), #> HINCP (dbl), PUMA (chr), ST (chr), TYPEHUGQ (chr), WGTP #> (dbl), PWGTP (dbl), WGTP1 (dbl), WGTP2 (dbl), WGTP3 #> (dbl), WGTP4 (dbl), WGTP5 (dbl), WGTP6 (dbl), WGTP7 #> (dbl), WGTP8 (dbl), WGTP9 (dbl), WGTP10 (dbl), WGTP11 #> (dbl), WGTP12 (dbl), WGTP13 (dbl), WGTP14 (dbl), WGTP15 #> (dbl), WGTP16 (dbl), WGTP17 (dbl), WGTP18 (dbl), WGTP19 #> (dbl), WGTP20 (dbl), WGTP21 (dbl), WGTP22 (dbl), WGTP23 #> (dbl), WGTP24 (dbl), WGTP25 (dbl), WGTP26 (dbl), WGTP27 #> (dbl), WGTP28 (dbl), WGTP29 (dbl), WGTP30 (dbl), WGTP31 #> (dbl), WGTP32 (dbl), WGTP33 (dbl), WGTP34 (dbl), WGTP35 #> (dbl), WGTP36 (dbl), WGTP37 (dbl), WGTP38 (dbl), WGTP39 #> (dbl), WGTP40 (dbl), WGTP41 (dbl), WGTP42 (dbl), WGTP43 #> (dbl), WGTP44 (dbl), WGTP45 (dbl), WGTP46 (dbl), WGTP47 #> (dbl), WGTP48 (dbl), WGTP49 (dbl), WGTP50 (dbl), WGTP51 #> (dbl), WGTP52 (dbl), WGTP53 (dbl), WGTP54 (dbl), WGTP55 #> (dbl), WGTP56 (dbl), WGTP57 (dbl), WGTP58 (dbl), WGTP59 #> (dbl), WGTP60 (dbl), WGTP61 (dbl), WGTP62 (dbl), WGTP63 #> (dbl), WGTP64 (dbl), WGTP65 (dbl), WGTP66 (dbl), WGTP67 #> (dbl), WGTP68 (dbl), WGTP69 (dbl), WGTP70 (dbl), WGTP71 #> (dbl), WGTP72 (dbl), WGTP73 (dbl), WGTP74 (dbl), WGTP75 #> (dbl), WGTP76 (dbl), WGTP77 (dbl), WGTP78 (dbl), WGTP79 #> (dbl), WGTP80 (dbl) des_acs %>% group_by(BDSP) %>% summary() #> Call: Called via srvyr #> Unstratified cluster jacknife (JK1) with 80 replicates and MSE variances. #> Sampling variables: #> - repweights: `WGTP1 + WGTP2 + WGTP3 + WGTP4 + WGTP5 + #> WGTP6 + WGTP7 + WGTP8 + WGTP9 + WGTP10 + WGTP11 + #> WGTP12 + WGTP13 + WGTP14 + WGTP15 + WGTP16 + WGTP17 + #> WGTP18 + WGTP19 + WGTP20 + WGTP21 + WGTP22 + WGTP23 + #> WGTP24 + WGTP25 + WGTP26 + WGTP27 + WGTP28 + WGTP29 + #> WGTP30 + WGTP31 + WGTP32 + WGTP33 + WGTP34 + WGTP35 + #> WGTP36 + WGTP37 + WGTP38 + WGTP39 + WGTP40 + WGTP41 + #> WGTP42 + WGTP43 + WGTP44 + WGTP45 + WGTP46 + WGTP47 + #> WGTP48 + WGTP49 + WGTP50 + WGTP51 + WGTP52 + WGTP53 + #> WGTP54 + WGTP55 + WGTP56 + WGTP57 + WGTP58 + WGTP59 + #> WGTP60 + WGTP61 + WGTP62 + WGTP63 + WGTP64 + WGTP65 + #> WGTP66 + WGTP67 + WGTP68 + WGTP69 + WGTP70 + WGTP71 + #> WGTP72 + WGTP73 + WGTP74 + WGTP75 + WGTP76 + WGTP77 + #> WGTP78 + WGTP79 + WGTP80` #> - weights: WGTP #> Grouping variables: #> - BDSP #> Data variables: #> - SERIALNO (chr), SPORDER (dbl), NP (dbl), BDSP (dbl), #> HINCP (dbl), PUMA (chr), ST (chr), TYPEHUGQ (chr), WGTP #> (dbl), PWGTP (dbl), WGTP1 (dbl), WGTP2 (dbl), WGTP3 #> (dbl), WGTP4 (dbl), WGTP5 (dbl), WGTP6 (dbl), WGTP7 #> (dbl), WGTP8 (dbl), WGTP9 (dbl), WGTP10 (dbl), WGTP11 #> (dbl), WGTP12 (dbl), WGTP13 (dbl), WGTP14 (dbl), WGTP15 #> (dbl), WGTP16 (dbl), WGTP17 (dbl), WGTP18 (dbl), WGTP19 #> (dbl), WGTP20 (dbl), WGTP21 (dbl), WGTP22 (dbl), WGTP23 #> (dbl), WGTP24 (dbl), WGTP25 (dbl), WGTP26 (dbl), WGTP27 #> (dbl), WGTP28 (dbl), WGTP29 (dbl), WGTP30 (dbl), WGTP31 #> (dbl), WGTP32 (dbl), WGTP33 (dbl), WGTP34 (dbl), WGTP35 #> (dbl), WGTP36 (dbl), WGTP37 (dbl), WGTP38 (dbl), WGTP39 #> (dbl), WGTP40 (dbl), WGTP41 (dbl), WGTP42 (dbl), WGTP43 #> (dbl), WGTP44 (dbl), WGTP45 (dbl), WGTP46 (dbl), WGTP47 #> (dbl), WGTP48 (dbl), WGTP49 (dbl), WGTP50 (dbl), WGTP51 #> (dbl), WGTP52 (dbl), WGTP53 (dbl), WGTP54 (dbl), WGTP55 #> (dbl), WGTP56 (dbl), WGTP57 (dbl), WGTP58 (dbl), WGTP59 #> (dbl), WGTP60 (dbl), WGTP61 (dbl), WGTP62 (dbl), WGTP63 #> (dbl), WGTP64 (dbl), WGTP65 (dbl), WGTP66 (dbl), WGTP67 #> (dbl), WGTP68 (dbl), WGTP69 (dbl), WGTP70 (dbl), WGTP71 #> (dbl), WGTP72 (dbl), WGTP73 (dbl), WGTP74 (dbl), WGTP75 #> (dbl), WGTP76 (dbl), WGTP77 (dbl), WGTP78 (dbl), WGTP79 #> (dbl), WGTP80 (dbl) #> Variables: #> [1] "SERIALNO" "SPORDER" "NP" "BDSP" "HINCP" #> [6] "PUMA" "ST" "TYPEHUGQ" "WGTP" "PWGTP" #> [11] "WGTP1" "WGTP2" "WGTP3" "WGTP4" "WGTP5" #> [16] "WGTP6" "WGTP7" "WGTP8" "WGTP9" "WGTP10" #> [21] "WGTP11" "WGTP12" "WGTP13" "WGTP14" "WGTP15" #> [26] "WGTP16" "WGTP17" "WGTP18" "WGTP19" "WGTP20" #> [31] "WGTP21" "WGTP22" "WGTP23" "WGTP24" "WGTP25" #> [36] "WGTP26" "WGTP27" "WGTP28" "WGTP29" "WGTP30" #> [41] "WGTP31" "WGTP32" "WGTP33" "WGTP34" "WGTP35" #> [46] "WGTP36" "WGTP37" "WGTP38" "WGTP39" "WGTP40" #> [51] "WGTP41" "WGTP42" "WGTP43" "WGTP44" "WGTP45" #> [56] "WGTP46" "WGTP47" "WGTP48" "WGTP49" "WGTP50" #> [61] "WGTP51" "WGTP52" "WGTP53" "WGTP54" "WGTP55" #> [66] "WGTP56" "WGTP57" "WGTP58" "WGTP59" "WGTP60" #> [71] "WGTP61" "WGTP62" "WGTP63" "WGTP64" "WGTP65" #> [76] "WGTP66" "WGTP67" "WGTP68" "WGTP69" "WGTP70" #> [81] "WGTP71" "WGTP72" "WGTP73" "WGTP74" "WGTP75" #> [86] "WGTP76" "WGTP77" "WGTP78" "WGTP79" "WGTP80" # Other designs library(survey) #> Loading required package: grid #> Loading required package: Matrix #> #> Attaching package: 'Matrix' #> The following objects are masked from 'package:tidyr': #> #> expand, pack, unpack #> Loading required package: survival #> #> Attaching package: 'survey' #> The following object is masked from 'package:graphics': #> #> dotchart data(api) apistrat %>% as_survey_design(strata = stype, weights = pw) #> Stratified Independent Sampling design (with replacement) #> Called via srvyr #> Sampling variables: #> - ids: `1` #> - strata: stype #> - weights: pw #> Data variables: #> - cds (chr), stype (fct), name (chr), sname (chr), snum #> (dbl), dname (chr), dnum (int), cname (chr), cnum #> (int), flag (int), pcttest (int), api00 (int), api99 #> (int), target (int), growth (int), sch.wide (fct), #> comp.imp (fct), both (fct), awards (fct), meals (int), #> ell (int), yr.rnd (fct), mobility (int), acs.k3 (int), #> acs.46 (int), acs.core (int), pct.resp (int), not.hsg #> (int), hsg (int), some.col (int), col.grad (int), #> grad.sch (int), avg.ed (dbl), full (int), emer (int), #> enroll (int), api.stu (int), pw (dbl), fpc (dbl) apiclus1 %>% as_survey_design(dnum, weights = pw, fpc = fpc) #> 1 - level Cluster Sampling design #> With (15) clusters. #> Called via srvyr #> Sampling variables: #> - ids: dnum #> - fpc: fpc #> - weights: pw #> Data variables: #> - cds (chr), stype (fct), name (chr), sname (chr), snum #> (dbl), dname (chr), dnum (int), cname (chr), cnum #> (int), flag (int), pcttest (int), api00 (int), api99 #> (int), target (int), growth (int), sch.wide (fct), #> comp.imp (fct), both (fct), awards (fct), meals (int), #> ell (int), yr.rnd (fct), mobility (int), acs.k3 (int), #> acs.46 (int), acs.core (int), pct.resp (int), not.hsg #> (int), hsg (int), some.col (int), col.grad (int), #> grad.sch (int), avg.ed (dbl), full (int), emer (int), #> enroll (int), api.stu (int), fpc (dbl), pw (dbl) apiclus2 %>% as_survey_design(c(dnum, snum), fpc = c(fpc1, fpc2)) #> 2 - level Cluster Sampling design #> With (40, 126) clusters. #> Called via srvyr #> Sampling variables: #> - ids: `dnum + snum` #> - fpc: `fpc1 + fpc2` #> Data variables: #> - cds (chr), stype (fct), name (chr), sname (chr), snum #> (dbl), dname (chr), dnum (int), cname (chr), cnum #> (int), flag (int), pcttest (int), api00 (int), api99 #> (int), target (int), growth (int), sch.wide (fct), #> comp.imp (fct), both (fct), awards (fct), meals (int), #> ell (int), yr.rnd (fct), mobility (int), acs.k3 (int), #> acs.46 (int), acs.core (int), pct.resp (int), not.hsg #> (int), hsg (int), some.col (int), col.grad (int), #> grad.sch (int), avg.ed (dbl), full (int), emer (int), #> enroll (int), api.stu (int), pw (dbl), fpc1 (dbl), fpc2 #> (int[1d]) apistrat %>% as_survey_design(dnum, strata = stype, weights = pw, nest = TRUE) #> Stratified 1 - level Cluster Sampling design (with replacement) #> With (162) clusters. #> Called via srvyr #> Sampling variables: #> - ids: dnum #> - strata: stype #> - weights: pw #> Data variables: #> - cds (chr), stype (fct), name (chr), sname (chr), snum #> (dbl), dname (chr), dnum (int), cname (chr), cnum #> (int), flag (int), pcttest (int), api00 (int), api99 #> (int), target (int), growth (int), sch.wide (fct), #> comp.imp (fct), both (fct), awards (fct), meals (int), #> ell (int), yr.rnd (fct), mobility (int), acs.k3 (int), #> acs.46 (int), acs.core (int), pct.resp (int), not.hsg #> (int), hsg (int), some.col (int), col.grad (int), #> grad.sch (int), avg.ed (dbl), full (int), emer (int), #> enroll (int), api.stu (int), pw (dbl), fpc (dbl) data(election) election_pps %>% as_survey_design(fpc = p, pps = "brewer") #> Independent Sampling design #> Called via srvyr #> Sampling variables: #> - ids: `1` #> - fpc: p #> Data variables: #> - County (fct), TotPrecincts (int), PrecinctsReporting #> (int), Bush (int), Kerry (int), Nader (int), votes #> (int), p (dbl), wt (dbl) # When creating a replicate object from design object, there are no sampling variables! ex1 <- apistrat %>% as_survey_design(strata = stype, weights = pw) %>% as_survey_rep() ex1 #> Call: Called via srvyr #> Stratified cluster jackknife (JKn) with 200 replicates. #> Data variables: #> - cds (chr), stype (fct), name (chr), sname (chr), snum #> (dbl), dname (chr), dnum (int), cname (chr), cnum #> (int), flag (int), pcttest (int), api00 (int), api99 #> (int), target (int), growth (int), sch.wide (fct), #> comp.imp (fct), both (fct), awards (fct), meals (int), #> ell (int), yr.rnd (fct), mobility (int), acs.k3 (int), #> acs.46 (int), acs.core (int), pct.resp (int), not.hsg #> (int), hsg (int), some.col (int), col.grad (int), #> grad.sch (int), avg.ed (dbl), full (int), emer (int), #> enroll (int), api.stu (int), pw (dbl), fpc (dbl) attr(ex1, "survey_vars") #> Sampling variables: ex2 <- apiclus1 %>% as_survey_design(dnum, weights = pw, fpc = fpc) %>% as_survey_rep() ex2 #> Call: Called via srvyr #> Unstratified cluster jacknife (JK1) with 15 replicates. #> Data variables: #> - cds (chr), stype (fct), name (chr), sname (chr), snum #> (dbl), dname (chr), dnum (int), cname (chr), cnum #> (int), flag (int), pcttest (int), api00 (int), api99 #> (int), target (int), growth (int), sch.wide (fct), #> comp.imp (fct), both (fct), awards (fct), meals (int), #> ell (int), yr.rnd (fct), mobility (int), acs.k3 (int), #> acs.46 (int), acs.core (int), pct.resp (int), not.hsg #> (int), hsg (int), some.col (int), col.grad (int), #> grad.sch (int), avg.ed (dbl), full (int), emer (int), #> enroll (int), api.stu (int), fpc (dbl), pw (dbl) attr(ex2, "survey_vars") #> Sampling variables:
Created on 2023-09-10 with reprex v2.0.2
Awesome, thanks!
gergness
commented
11 months ago
This addresses #162
It also removes some odd //n characters that are in the replicate weights. I cannot figure out where these are added in the code so I hack it to remove them before printing. There's probably a better solution.
Some examples below but no formal tests:
Created on 2023-09-10 with reprex v2.0.2