Structural topic model (STM) is an unsupervised machine learning method for text analysis, leveraging on the metadata (i.e., author, date and ideology) to detect different topics of document.
STM is particularly popular among social scientists. For example, a research published in Policy and Society employs this method to detect different policy responses to COVID-19 globally.
We utilize stm package to build structural topic models, to learn more about this package see its home page. Full tutorial for beginners see here.
require(pacman) # package management
p_load(stm, ggthemes, SnowballC, stopwords, pluralize, stm, ldatuning, stopwords, quanteda, tm, textclean, stringr, reticulate, purrr, furrr, progress, tictoc, lubridate, progress, rio, tidyverse, RSelenium, rvest, foreach, tryCatchLog, stringi, cld2, tidytext, quanteda, tidyfst, httr, tictoc, miceadds, sandwich, urltools) We introduce two covariates to build STM: Belt and Road Initiative (BRI) and date.
import("D:/OneDrive - HKUST Connect/桌面/Ra_Hong/BRI_country.xlsx", setclass = "tibble") %>%
select(Country, BRI_dummy) %>%
set_names(c("country_name", "BRI_dummy")) %>%
mutate(across(country_name, str_trim)) %>%
right_join(mutate(raw, across(country_name, str_trim)), "country_name") %>%
mutate(category = case_when(BRI_dummy == 1 ~ "BRI",
is.na(BRI_dummy) ~ "Non-BRI"),
BRI_dummy = NULL) -> rawWe have tried all mainstream translation APIs including Google, DeepL and Baidu. Google is the best regarding quality and coverage. Nevertheless, considering our huge usage, all of them are too expensive to afford.
Many Python packages provide unofficial Google translate API, low translation quality is by no means the only problem facing these free APIs, but it is one of the most pernicious. I tried them one by one, and find the only useful is easygoogletranslate.
How to import easygoogletranslate into R? We can call Python from R using reticulate package. Or, we can convert its Python source code to R code.
translator <- function(target_language, text, timeout) {
sprintf('https://translate.google.com/m?sl=auto&tl=%s&q=%s', target_language, url_encode(text)) %>%
GET(timeout(timeout)) %>%
read_html(encoding = "utf-8") %>%
html_element(xpath = "//div[@class='result-container']") %>%
html_text()} # our translator
plan(multisession, workers = 16) # using 16 cou cores
trans <- possibly(.f = translator$translate, otherwise = "error!") # error handling
text %>%
mutate(translation = future_map_chr(text, ~ trans("en", . , 5))) -> test # parallell translatinguse_python("C:\\Users\\Python\\Python310") # specify the python
reticulate::import("easygoogletranslate") -> EasyGoogleTranslate # import python module
EasyGoogleTranslate$EasyGoogleTranslate(target_language = "en", timeout = 10) -> translator
trans <- possibly(.f = translator$translate, otherwise = "error!") # error handling
text %>%
mutate(translation = modify(sub_contents, ~ trans(.))) -> textuse proxy when parallel translating. see use_proxy.
After many rounds of testing, translation outcome is consist with official API. See example:
translator <- function(target_language, text, timeout) {
sprintf('https://translate.google.com/m?sl=auto&tl=%s&q=%s', target_language, url_encode(text)) %>%
GET(timeout(timeout)) %>%
read_html(encoding = "utf-8") %>%
html_element(xpath = "//div[@class='result-container']") %>%
html_text()}
translator("en", "홍콩은 중국 본토와 다른 방역 조치를 취하기로 결정했습니다", 5) # from ko to en[1] "Hong Kong has decided to take different quarantine measures than mainland China"Due to Google restrictions, the text must be equal to or less than 5000 character. We have to split text into 5000 characters to translate more.
split_text <- function(text) {text %>%
str_locate_all("[:punct:]") %>%
.[[1]] %>%
.[, 1] %>%
.[-length(.)] -> punc_locaiton
if_else(str_length(text) %% 500 > 300, (str_length(text) %/% 500) + 1, str_length(text) %/% 500) -> seg_n
seq(str_length(text) / seg_n, str_length(text), (str_length(text) / seg_n)) %>%
.[-length(.)] -> point
punc_locaiton %>%
tibble(location = .) %>%
mutate(distance = map(location, ~ abs(. - point)) |> map_dbl(~ min(unlist(.)))) %>%
slice_min(distance, n = seg_n - 1) %>%
pull(location) %>%
sort() -> cut_points
for (i in 1:length(cut_points)) {
str_sub(text, (cut_points[i] + 5*(i-1)), ((cut_points[i] + 1) + 5*(i-1))) <- " %cut% "
}
str_split_fixed(text, " %cut% ", seg_n) %>%
.[1,] -> text
return(text)} # try different number We have to clean text for machine learning. For example, replace contraction to their multi-word forms. Moreover, for these Chinese names like Peng Shuai, we can replace it with Peng_Shuai, so tokenizer will not break Peng Shuai into two components.
clean_text <- function(x) {x %>%
replace_html() %>%
replace_non_ascii(replacement = " ") %>%
replace_contraction() %>% # replace contraction to their multi-word forms
replace_url() %>%
str_replace_all("\\b5G\\b", "fiveg") %>%
replace_email(replacement = " ") %>%
replace_date(replacement = " ") %>%
replace_time(replacement = " ") %>%
str_replace_all(pattern = "[[:punct:]]", " ") %>% # remove punctuation
str_replace_all(pattern = "[^\\s]*[0-9][^\\s]*", " ") %>% # remove mixed string n number
str_replace_all("[$&+,:;=?@#|'<>.^*()%!]", " ") %>%
str_squish() %>%
str_trim() %>%
str_to_lower() %>%
replace_white() %>%
replace_kern() %>%
str_replace_all("co\\s*ltd|\\binc\\b", " ") %>%
str_replace_all("(zhang)*\\s*gao\\s*li\\s*(zhang)*", "zhang_gao_li ") %>%
str_replace_all("(peng)*\\s*shuai\\s*(peng)*", "peng_shuai ") %>%
str_replace_all("(xi)*\\s*jin\\s*ping\\s*(xi)*|\\bxi\\b", "xi_jin_ping ") %>%
str_replace_all("communist\\s*party", "communist_party ")%>%
str_replace_all("hong\\s*kong", "hong_kong ") %>%
str_replace_all("united\\s*states|u\\s+s", "america ") %>%
str_replace_all("united\\s*kingdom|u\\s+k", "britain ") %>%
str_replace_all("north\\s*korea", "north_korea ") %>%
str_replace_all("south\\s*korea", "south_korea ") %>%
str_replace_all("joe\\s*biden", "joe_biden") %>%
str_replace_all("\\b\\w{1,2}\\b", " ") %>%
str_squish()}Since we got 1.08 million cases, use all data will be computational expensive. So we select 50000 cases thorough random sampling. Moreover, we convert date to interger from 1 to 62 since our data covered two months.
raw %>%
slice(sample(1:nrow(.), 50000)) %>%
mutate(id = sprintf('news%s', 1:nrow(.))) %>%
select(id, code, date, country_name, translation, category) %>%
mutate(day = as.character(date) |> str_extract("(\\d{1}-\\d{2})$"),
day = case_when(str_extract(day, "^\\d") == 0 ~ as.numeric(str_extract(day, "\\d{2}$")),
str_extract(day, "^\\d") == 1 ~ as.numeric(str_extract(day, "\\d{2}$")) + 31,
str_extract(day, "^\\d") == 2 ~ as.numeric(str_extract(day, "\\d{2}$")) + 60)) -> test
test %>%
mutate(text = future_map_chr(translation, clean_text)) -> test # text cleaningtest %>%
unnest_tokens(word, text) %>%
drop_na() -> test_tokens
test_tokens %>%
distinct(word) %>%
mutate(word_length = str_length(word)) -> word_length
test_tokens %>%
count_dt(id, word, sort = T) -> news_words
news_words %>%
group_by(id) %>%
summarise(total = sum(n)) -> total_words
news_words %>%
left_join(total_words) -> news_words
news_words %>%
bind_tf_idf(word, id, n) -> test_tf_idftest_tf_idf %>%
group_by(id) %>%
group_map(~ pull(slice_min(.x, tf_idf, n = 2L), word)) %>%
unlist() %>%
unique() -> stopwords.x
test_tokens %>%
count(word, sort = T) -> word_fre
word_fre %>%
filter(n < 2 | n > 20000) %>%
pull(word) -> stopwords.y
word_length %>%
filter(word_length <= 2 | word_length >= 20) %>%
pull(word) %>%
unlist() -> stopwords.z
c(stopwords::stopwords(source ="smart"), stopwords.x, stopwords.y, stopwords.z) %>%
unique() %>%
tibble(word = .) -> stopwords_for_ldaHow to choose K is one of the most challenging part of unsupervised methods. See Julia Silge’s blog. We have fit topic models with different K from 10 to 140. We also use spline function to perform non-linear transformations of the date variable.
plan(multisession, workers = 16)
test_tokens %>%
anti_join(stopwords_for_lda, by = "word") %>%
mutate(word = future_map_chr(word, wordStem)) -> test_tokens # stemming
test_tokens %>%
count_dt(id, word, .name = "count") %>%
cast_sparse(id, word, count) -> sparse
test_tokens %>%
sample_frac() %>%
distinct(id, category, day) -> covariates # cagegory means BRI countries or not
tic()
tibble(K = seq(10, 140, 10)) %>%
mutate(topic_model = future_map(K, ~ stm(sparse,
K = .,
prevalence = ~category + s(day) # 10-spline,
data = covariates,
verbose = FALSE,
init.type = "Spectral"))) -> topic_models
toc()
heldout <- make.heldout(sparse)
tic()
topic_models %>%
mutate(exclusivity = map(topic_model, exclusivity),
semantic_coherence = map(topic_model, semanticCoherence, sparse),
eval_heldout = map(topic_model, eval.heldout, heldout$missing),
residual = map(topic_model, checkResiduals, sparse),
bound = map_dbl(topic_model, function(x) max(x$convergence$bound)),
lfact = map_dbl(topic_model, function(x) lfactorial(x$settings$dim$K)),
lbound = bound + lfact,
iterations = map_dbl(topic_model, function(x) length(x$convergence$bound))) -> find_k
toc()A topic model with 40 topics is better.
Highest word probabilities for each topic:
load("D:/OneDrive - HKUST Connect/SOSC/paper_with_jean/topic_models_40.Rdata")
tidy(topic_models_40) %>%
group_by(topic) %>%
top_n(10, beta) %>%
ungroup() %>%
mutate(topic = str_c("Topic ", topic),
term = reorder_within(term, beta, topic)) %>%
ggplot(aes(term, beta, fill = as_factor(topic))) +
geom_col(alpha = 0.5, show.legend = FALSE) +
facet_wrap(~ topic, scales = "free_y") +
coord_flip() +
scale_x_reordered() +
labs(x = NULL, y = expression(beta)
ggthemes::theme_economist_white() 
|> Topic 11 is about Peng Shuai Event
load("D:/OneDrive - HKUST Connect/SOSC/paper_with_jean/topic_models_40.Rdata")
labelTopics(topic_models_40, 11)Topic 11 Top Words:
Highest Prob: polic, olymp, investig, call, tenni, player, accus
FREX: tenni, peng_shuai, wta, zhang_gao_li, fentanyl, metoo, djokov
Lift: pirro, myre, youngkin, badiucao, gabbi, baumgarten, fleischer
Score: peng_shuai, wta, tenni, polic, olymp, zhang_gao_li, biden |> Topic 15 is about The North Korean Nuclear Issue
labelTopics(topic_models_40, 15)Topic 15 Top Words:
Highest Prob: militari, nuclear, defens, press, releas, sea, air
FREX: missil, hyperson, warhead, pyongyang, ladakh, destroy, adiz
Lift: carestor, plutonium, adiz, superjumbo, seawolf, iuu, lonapegsomatropin
Score: missil, militari, nuclear, north_korea, submarin, weapon, hyperson |> Topic 24 is about Situation Across the Taiwan Strait
labelTopics(topic_models_40, 24)Topic 24 Top Words:
Highest Prob: elect, polit, minist, xi_jin_p, democrat, relat, strait
FREX: kishida, kuomintang, dpp, hiroshima, ldp, yamaguchi, komeito
Lift: ritsumin, inec, ihiala, ikka, bva, hiroshima, chyddi
Score: kishida, strait, tsai, democraci, kuomintang, democrat, minist We performs a regression where topic-proportions are the outcome variable. So we can explore topic prevalence given document traits.
load("D:/OneDrive - HKUST Connect/SOSC/paper_with_jean/covariates_40.Rdata")
prep <- estimateEffect(1:40 ~ category * s(day), topic_models_40, metadata = covariates, uncertainty = "None")
summary(prep)
##
## Call:
## estimateEffect(formula = 1:40 ~ category * s(day), stmobj = topic_models_40,
## metadata = covariates, uncertainty = "None")
##
##
## Topic 1:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0084485 0.0046913 1.801 0.0717 .
## categoryNon-BRI 0.0046678 0.0054412 0.858 0.3910
## s(day)1 0.0043254 0.0078523 0.551 0.5817
## s(day)2 0.0045527 0.0050937 0.894 0.3714
## s(day)3 0.0007939 0.0056805 0.140 0.8888
## s(day)4 0.0014042 0.0050606 0.277 0.7814
## s(day)5 0.0003789 0.0051862 0.073 0.9418
## s(day)6 0.0034253 0.0053420 0.641 0.5214
## s(day)7 0.0010709 0.0054399 0.197 0.8439
## s(day)8 0.0045522 0.0058813 0.774 0.4389
## s(day)9 0.0068206 0.0059822 1.140 0.2542
## s(day)10 -0.0038648 0.0054991 -0.703 0.4822
## categoryNon-BRI:s(day)1 -0.0044571 0.0093472 -0.477 0.6335
## categoryNon-BRI:s(day)2 -0.0085174 0.0058481 -1.456 0.1453
## categoryNon-BRI:s(day)3 -0.0013049 0.0065606 -0.199 0.8423
## categoryNon-BRI:s(day)4 -0.0026424 0.0058130 -0.455 0.6494
## categoryNon-BRI:s(day)5 -0.0043664 0.0060333 -0.724 0.4692
## categoryNon-BRI:s(day)6 -0.0038430 0.0062352 -0.616 0.5377
## categoryNon-BRI:s(day)7 -0.0009763 0.0064732 -0.151 0.8801
## categoryNon-BRI:s(day)8 -0.0087829 0.0067434 -1.302 0.1928
## categoryNon-BRI:s(day)9 -0.0057723 0.0069823 -0.827 0.4084
## categoryNon-BRI:s(day)10 0.0014102 0.0065046 0.217 0.8284
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 2:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.033575 0.019955 1.683 0.09246 .
## categoryNon-BRI 0.016640 0.023194 0.717 0.47312
## s(day)1 0.070751 0.035196 2.010 0.04442 *
## s(day)2 -0.004318 0.021189 -0.204 0.83854
## s(day)3 0.061493 0.024768 2.483 0.01304 *
## s(day)4 -0.033800 0.021523 -1.570 0.11633
## s(day)5 0.239084 0.022476 10.637 < 2e-16 ***
## s(day)6 -0.096728 0.023455 -4.124 3.73e-05 ***
## s(day)7 0.116030 0.024089 4.817 1.46e-06 ***
## s(day)8 -0.056341 0.025438 -2.215 0.02678 *
## s(day)9 0.115842 0.025858 4.480 7.48e-06 ***
## s(day)10 0.127705 0.024100 5.299 1.17e-07 ***
## categoryNon-BRI:s(day)1 -0.042671 0.041170 -1.036 0.29999
## categoryNon-BRI:s(day)2 0.006801 0.024073 0.283 0.77756
## categoryNon-BRI:s(day)3 -0.049464 0.029322 -1.687 0.09163 .
## categoryNon-BRI:s(day)4 0.035077 0.025075 1.399 0.16184
## categoryNon-BRI:s(day)5 -0.184014 0.026680 -6.897 5.37e-12 ***
## categoryNon-BRI:s(day)6 0.068185 0.026612 2.562 0.01041 *
## categoryNon-BRI:s(day)7 -0.065492 0.028296 -2.315 0.02064 *
## categoryNon-BRI:s(day)8 0.039261 0.029505 1.331 0.18331
## categoryNon-BRI:s(day)9 -0.072445 0.030877 -2.346 0.01897 *
## categoryNon-BRI:s(day)10 -0.083288 0.028149 -2.959 0.00309 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 3:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.076e-03 2.329e-03 0.891 0.373
## categoryNon-BRI 2.498e-04 2.592e-03 0.096 0.923
## s(day)1 -1.436e-03 4.014e-03 -0.358 0.720
## s(day)2 7.506e-04 2.475e-03 0.303 0.762
## s(day)3 1.770e-04 2.830e-03 0.063 0.950
## s(day)4 1.132e-04 2.500e-03 0.045 0.964
## s(day)5 2.280e-04 2.554e-03 0.089 0.929
## s(day)6 -5.077e-04 2.680e-03 -0.189 0.850
## s(day)7 -1.061e-04 2.703e-03 -0.039 0.969
## s(day)8 -2.841e-04 2.823e-03 -0.101 0.920
## s(day)9 -2.484e-04 3.053e-03 -0.081 0.935
## s(day)10 1.815e-05 2.644e-03 0.007 0.995
## categoryNon-BRI:s(day)1 9.084e-04 4.459e-03 0.204 0.839
## categoryNon-BRI:s(day)2 -4.979e-04 2.892e-03 -0.172 0.863
## categoryNon-BRI:s(day)3 -1.150e-03 3.152e-03 -0.365 0.715
## categoryNon-BRI:s(day)4 7.935e-04 2.873e-03 0.276 0.782
## categoryNon-BRI:s(day)5 2.634e-04 2.893e-03 0.091 0.927
## categoryNon-BRI:s(day)6 1.350e-03 3.004e-03 0.449 0.653
## categoryNon-BRI:s(day)7 -1.150e-03 3.103e-03 -0.371 0.711
## categoryNon-BRI:s(day)8 5.460e-04 3.218e-03 0.170 0.865
## categoryNon-BRI:s(day)9 -1.660e-03 3.567e-03 -0.465 0.642
## categoryNon-BRI:s(day)10 1.270e-03 2.971e-03 0.427 0.669
##
##
## Topic 4:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.317e-04 2.173e-03 0.245 0.807
## categoryNon-BRI 6.177e-05 2.493e-03 0.025 0.980
## s(day)1 -7.990e-04 3.731e-03 -0.214 0.830
## s(day)2 7.123e-04 2.300e-03 0.310 0.757
## s(day)3 -5.010e-04 2.636e-03 -0.190 0.849
## s(day)4 1.430e-03 2.309e-03 0.619 0.536
## s(day)5 -7.778e-04 2.407e-03 -0.323 0.747
## s(day)6 1.447e-03 2.504e-03 0.578 0.563
## s(day)7 -5.192e-05 2.500e-03 -0.021 0.983
## s(day)8 5.579e-04 2.593e-03 0.215 0.830
## s(day)9 1.059e-03 2.781e-03 0.381 0.703
## s(day)10 5.764e-04 2.366e-03 0.244 0.808
## categoryNon-BRI:s(day)1 1.551e-03 4.301e-03 0.361 0.718
## categoryNon-BRI:s(day)2 -6.164e-04 2.622e-03 -0.235 0.814
## categoryNon-BRI:s(day)3 1.427e-03 3.049e-03 0.468 0.640
## categoryNon-BRI:s(day)4 -1.096e-04 2.742e-03 -0.040 0.968
## categoryNon-BRI:s(day)5 8.584e-05 2.777e-03 0.031 0.975
## categoryNon-BRI:s(day)6 1.568e-03 2.953e-03 0.531 0.595
## categoryNon-BRI:s(day)7 -6.060e-04 2.874e-03 -0.211 0.833
## categoryNon-BRI:s(day)8 1.295e-03 3.081e-03 0.420 0.674
## categoryNon-BRI:s(day)9 -1.142e-03 3.329e-03 -0.343 0.732
## categoryNon-BRI:s(day)10 -2.397e-04 2.805e-03 -0.085 0.932
##
##
## Topic 5:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0143462 0.0102061 1.406 0.160
## categoryNon-BRI 0.0043463 0.0117972 0.368 0.713
## s(day)1 0.0030062 0.0172830 0.174 0.862
## s(day)2 0.0024227 0.0107566 0.225 0.822
## s(day)3 0.0014556 0.0122058 0.119 0.905
## s(day)4 0.0051135 0.0112039 0.456 0.648
## s(day)5 0.0002099 0.0116156 0.018 0.986
## s(day)6 0.0047415 0.0122270 0.388 0.698
## s(day)7 0.0001150 0.0117554 0.010 0.992
## s(day)8 -0.0059255 0.0128719 -0.460 0.645
## s(day)9 0.0126441 0.0130423 0.969 0.332
## s(day)10 -0.0037899 0.0123247 -0.308 0.758
## categoryNon-BRI:s(day)1 -0.0046237 0.0199928 -0.231 0.817
## categoryNon-BRI:s(day)2 -0.0016679 0.0127014 -0.131 0.896
## categoryNon-BRI:s(day)3 -0.0039392 0.0144687 -0.272 0.785
## categoryNon-BRI:s(day)4 -0.0107785 0.0132913 -0.811 0.417
## categoryNon-BRI:s(day)5 0.0045660 0.0135578 0.337 0.736
## categoryNon-BRI:s(day)6 -0.0091544 0.0142942 -0.640 0.522
## categoryNon-BRI:s(day)7 0.0005078 0.0138556 0.037 0.971
## categoryNon-BRI:s(day)8 0.0031459 0.0152560 0.206 0.837
## categoryNon-BRI:s(day)9 -0.0157001 0.0153711 -1.021 0.307
## categoryNon-BRI:s(day)10 0.0021837 0.0144617 0.151 0.880
##
##
## Topic 6:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.057956 0.009365 6.189 6.12e-10 ***
## categoryNon-BRI -0.025956 0.010730 -2.419 0.01557 *
## s(day)1 -0.048379 0.015674 -3.087 0.00203 **
## s(day)2 -0.018087 0.010254 -1.764 0.07775 .
## s(day)3 -0.031366 0.011226 -2.794 0.00521 **
## s(day)4 -0.023112 0.009938 -2.326 0.02005 *
## s(day)5 -0.041389 0.010457 -3.958 7.57e-05 ***
## s(day)6 -0.021681 0.010904 -1.988 0.04678 *
## s(day)7 -0.025027 0.011045 -2.266 0.02345 *
## s(day)8 -0.037074 0.011732 -3.160 0.00158 **
## s(day)9 -0.025647 0.012403 -2.068 0.03867 *
## s(day)10 -0.031311 0.010996 -2.847 0.00441 **
## categoryNon-BRI:s(day)1 0.045773 0.018623 2.458 0.01398 *
## categoryNon-BRI:s(day)2 0.012259 0.012005 1.021 0.30718
## categoryNon-BRI:s(day)3 0.032711 0.013131 2.491 0.01274 *
## categoryNon-BRI:s(day)4 0.016460 0.011928 1.380 0.16762
## categoryNon-BRI:s(day)5 0.039219 0.012269 3.197 0.00139 **
## categoryNon-BRI:s(day)6 0.027486 0.012731 2.159 0.03085 *
## categoryNon-BRI:s(day)7 0.017333 0.012942 1.339 0.18051
## categoryNon-BRI:s(day)8 0.036919 0.013536 2.727 0.00639 **
## categoryNon-BRI:s(day)9 0.026949 0.014478 1.861 0.06269 .
## categoryNon-BRI:s(day)10 0.024391 0.012701 1.920 0.05482 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 7:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0203430 0.0070610 2.881 0.00397 **
## categoryNon-BRI 0.0019959 0.0082130 0.243 0.80799
## s(day)1 -0.0008431 0.0120974 -0.070 0.94444
## s(day)2 -0.0005220 0.0078179 -0.067 0.94676
## s(day)3 0.0080662 0.0085173 0.947 0.34363
## s(day)4 -0.0008619 0.0076237 -0.113 0.90999
## s(day)5 0.0134023 0.0079380 1.688 0.09134 .
## s(day)6 -0.0006484 0.0080507 -0.081 0.93581
## s(day)7 0.0068594 0.0085347 0.804 0.42157
## s(day)8 0.0110618 0.0086195 1.283 0.19938
## s(day)9 -0.0086827 0.0091682 -0.947 0.34362
## s(day)10 0.0161570 0.0081733 1.977 0.04807 *
## categoryNon-BRI:s(day)1 -0.0011847 0.0142127 -0.083 0.93357
## categoryNon-BRI:s(day)2 0.0066366 0.0091194 0.728 0.46677
## categoryNon-BRI:s(day)3 -0.0090318 0.0101102 -0.893 0.37168
## categoryNon-BRI:s(day)4 0.0021841 0.0088392 0.247 0.80483
## categoryNon-BRI:s(day)5 -0.0107905 0.0092836 -1.162 0.24511
## categoryNon-BRI:s(day)6 -0.0044382 0.0095624 -0.464 0.64255
## categoryNon-BRI:s(day)7 -0.0022539 0.0101575 -0.222 0.82440
## categoryNon-BRI:s(day)8 -0.0145370 0.0102127 -1.423 0.15462
## categoryNon-BRI:s(day)9 0.0146272 0.0110820 1.320 0.18687
## categoryNon-BRI:s(day)10 -0.0170123 0.0096636 -1.760 0.07834 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 8:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0249310 0.0079043 3.154 0.00161 **
## categoryNon-BRI -0.0012646 0.0089054 -0.142 0.88707
## s(day)1 0.0108297 0.0133452 0.812 0.41708
## s(day)2 -0.0021759 0.0083567 -0.260 0.79457
## s(day)3 0.0086530 0.0091497 0.946 0.34430
## s(day)4 0.0028253 0.0088429 0.319 0.74935
## s(day)5 0.0077519 0.0083091 0.933 0.35086
## s(day)6 0.0032122 0.0091881 0.350 0.72664
## s(day)7 0.0033618 0.0092326 0.364 0.71576
## s(day)8 0.0134269 0.0095136 1.411 0.15815
## s(day)9 0.0039906 0.0099475 0.401 0.68830
## s(day)10 0.0071380 0.0090652 0.787 0.43105
## categoryNon-BRI:s(day)1 -0.0028149 0.0151463 -0.186 0.85257
## categoryNon-BRI:s(day)2 0.0079627 0.0096085 0.829 0.40727
## categoryNon-BRI:s(day)3 0.0043288 0.0106154 0.408 0.68344
## categoryNon-BRI:s(day)4 0.0012807 0.0099530 0.129 0.89761
## categoryNon-BRI:s(day)5 -0.0011132 0.0097488 -0.114 0.90909
## categoryNon-BRI:s(day)6 0.0003955 0.0104747 0.038 0.96988
## categoryNon-BRI:s(day)7 0.0087295 0.0104806 0.833 0.40489
## categoryNon-BRI:s(day)8 -0.0083557 0.0112407 -0.743 0.45728
## categoryNon-BRI:s(day)9 -0.0045203 0.0112627 -0.401 0.68816
## categoryNon-BRI:s(day)10 0.0065877 0.0105436 0.625 0.53210
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 9:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.007613 0.001869 4.073 4.64e-05 ***
## categoryNon-BRI -0.003433 0.002152 -1.595 0.11062
## s(day)1 -0.010494 0.003211 -3.268 0.00108 **
## s(day)2 -0.002492 0.001928 -1.293 0.19617
## s(day)3 -0.005080 0.002285 -2.224 0.02619 *
## s(day)4 -0.005681 0.002006 -2.832 0.00463 **
## s(day)5 -0.005399 0.002101 -2.570 0.01018 *
## s(day)6 -0.005917 0.002065 -2.865 0.00417 **
## s(day)7 -0.004425 0.002239 -1.976 0.04814 *
## s(day)8 -0.005943 0.002258 -2.632 0.00850 **
## s(day)9 -0.006147 0.002359 -2.606 0.00916 **
## s(day)10 -0.005089 0.002188 -2.326 0.02002 *
## categoryNon-BRI:s(day)1 0.007487 0.003692 2.028 0.04259 *
## categoryNon-BRI:s(day)2 0.002453 0.002235 1.098 0.27232
## categoryNon-BRI:s(day)3 0.001746 0.002696 0.648 0.51720
## categoryNon-BRI:s(day)4 0.005106 0.002317 2.203 0.02758 *
## categoryNon-BRI:s(day)5 0.002214 0.002461 0.899 0.36840
## categoryNon-BRI:s(day)6 0.004422 0.002417 1.830 0.06732 .
## categoryNon-BRI:s(day)7 0.001958 0.002581 0.759 0.44806
## categoryNon-BRI:s(day)8 0.003805 0.002707 1.406 0.15985
## categoryNon-BRI:s(day)9 0.005255 0.002778 1.892 0.05855 .
## categoryNon-BRI:s(day)10 0.002779 0.002512 1.106 0.26855
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 10:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.038042 0.012433 3.060 0.00222 **
## categoryNon-BRI -0.001126 0.014247 -0.079 0.93701
## s(day)1 -0.012444 0.020839 -0.597 0.55041
## s(day)2 0.009195 0.013926 0.660 0.50908
## s(day)3 -0.006996 0.014614 -0.479 0.63213
## s(day)4 0.011131 0.013316 0.836 0.40319
## s(day)5 -0.016150 0.013850 -1.166 0.24359
## s(day)6 0.010871 0.013819 0.787 0.43148
## s(day)7 -0.005356 0.014501 -0.369 0.71188
## s(day)8 0.008424 0.015374 0.548 0.58374
## s(day)9 -0.012256 0.016306 -0.752 0.45227
## s(day)10 0.002972 0.014004 0.212 0.83195
## categoryNon-BRI:s(day)1 0.007639 0.024272 0.315 0.75296
## categoryNon-BRI:s(day)2 -0.006796 0.015223 -0.446 0.65528
## categoryNon-BRI:s(day)3 -0.000739 0.017221 -0.043 0.96577
## categoryNon-BRI:s(day)4 -0.013950 0.015124 -0.922 0.35632
## categoryNon-BRI:s(day)5 0.014391 0.016505 0.872 0.38325
## categoryNon-BRI:s(day)6 -0.013577 0.015823 -0.858 0.39085
## categoryNon-BRI:s(day)7 0.010665 0.017462 0.611 0.54136
## categoryNon-BRI:s(day)8 -0.007297 0.017814 -0.410 0.68209
## categoryNon-BRI:s(day)9 0.010996 0.019075 0.576 0.56429
## categoryNon-BRI:s(day)10 0.001344 0.016723 0.080 0.93592
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 11:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.032966 0.010823 3.046 0.00232 **
## categoryNon-BRI 0.003349 0.012484 0.268 0.78851
## s(day)1 -0.001182 0.017984 -0.066 0.94760
## s(day)2 0.007251 0.011760 0.617 0.53749
## s(day)3 -0.013247 0.012631 -1.049 0.29427
## s(day)4 0.010219 0.011877 0.860 0.38957
## s(day)5 -0.020593 0.011879 -1.734 0.08301 .
## s(day)6 0.019976 0.012720 1.571 0.11630
## s(day)7 -0.015457 0.012244 -1.262 0.20680
## s(day)8 0.017413 0.013538 1.286 0.19839
## s(day)9 -0.018413 0.014063 -1.309 0.19043
## s(day)10 0.005609 0.012721 0.441 0.65925
## categoryNon-BRI:s(day)1 -0.009632 0.021456 -0.449 0.65350
## categoryNon-BRI:s(day)2 -0.006283 0.013678 -0.459 0.64600
## categoryNon-BRI:s(day)3 0.005612 0.014841 0.378 0.70531
## categoryNon-BRI:s(day)4 -0.009392 0.013911 -0.675 0.49957
## categoryNon-BRI:s(day)5 0.013249 0.013767 0.962 0.33584
## categoryNon-BRI:s(day)6 -0.022021 0.014921 -1.476 0.13998
## categoryNon-BRI:s(day)7 0.008308 0.014283 0.582 0.56079
## categoryNon-BRI:s(day)8 -0.016821 0.015770 -1.067 0.28614
## categoryNon-BRI:s(day)9 0.015277 0.016850 0.907 0.36459
## categoryNon-BRI:s(day)10 -0.010817 0.014961 -0.723 0.46964
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 12:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0382841 0.0168125 2.277 0.0228 *
## categoryNon-BRI 0.0008240 0.0190462 0.043 0.9655
## s(day)1 -0.0091477 0.0287398 -0.318 0.7503
## s(day)2 0.0032659 0.0185324 0.176 0.8601
## s(day)3 -0.0031375 0.0197782 -0.159 0.8740
## s(day)4 0.0088822 0.0182820 0.486 0.6271
## s(day)5 -0.0166392 0.0184374 -0.902 0.3668
## s(day)6 0.0032616 0.0185768 0.176 0.8606
## s(day)7 0.0003815 0.0194980 0.020 0.9844
## s(day)8 -0.0028767 0.0202303 -0.142 0.8869
## s(day)9 -0.0231554 0.0212365 -1.090 0.2756
## s(day)10 -0.0065601 0.0193028 -0.340 0.7340
## categoryNon-BRI:s(day)1 0.0157926 0.0326131 0.484 0.6282
## categoryNon-BRI:s(day)2 -0.0076241 0.0208968 -0.365 0.7152
## categoryNon-BRI:s(day)3 0.0054954 0.0228662 0.240 0.8101
## categoryNon-BRI:s(day)4 -0.0134391 0.0207165 -0.649 0.5165
## categoryNon-BRI:s(day)5 0.0188353 0.0217528 0.866 0.3866
## categoryNon-BRI:s(day)6 -0.0055526 0.0215488 -0.258 0.7967
## categoryNon-BRI:s(day)7 0.0025170 0.0221962 0.113 0.9097
## categoryNon-BRI:s(day)8 -0.0022679 0.0236564 -0.096 0.9236
## categoryNon-BRI:s(day)9 0.0290760 0.0247055 1.177 0.2392
## categoryNon-BRI:s(day)10 -0.0078536 0.0226529 -0.347 0.7288
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 13:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.603e-02 1.131e-02 2.302 0.0213 *
## categoryNon-BRI 1.148e-02 1.307e-02 0.878 0.3798
## s(day)1 4.546e-03 1.952e-02 0.233 0.8158
## s(day)2 2.116e-02 1.226e-02 1.726 0.0843 .
## s(day)3 2.983e-03 1.398e-02 0.213 0.8310
## s(day)4 1.518e-02 1.209e-02 1.255 0.2094
## s(day)5 -5.953e-03 1.268e-02 -0.469 0.6388
## s(day)6 1.173e-02 1.328e-02 0.884 0.3769
## s(day)7 8.180e-03 1.324e-02 0.618 0.5367
## s(day)8 1.396e-02 1.436e-02 0.972 0.3310
## s(day)9 6.412e-03 1.431e-02 0.448 0.6540
## s(day)10 -2.711e-03 1.328e-02 -0.204 0.8382
## categoryNon-BRI:s(day)1 -6.852e-03 2.298e-02 -0.298 0.7656
## categoryNon-BRI:s(day)2 -3.182e-02 1.425e-02 -2.232 0.0256 *
## categoryNon-BRI:s(day)3 2.554e-03 1.626e-02 0.157 0.8752
## categoryNon-BRI:s(day)4 -2.547e-02 1.383e-02 -1.842 0.0655 .
## categoryNon-BRI:s(day)5 -2.804e-03 1.506e-02 -0.186 0.8523
## categoryNon-BRI:s(day)6 -1.221e-02 1.573e-02 -0.776 0.4377
## categoryNon-BRI:s(day)7 -1.241e-02 1.575e-02 -0.788 0.4306
## categoryNon-BRI:s(day)8 -1.949e-02 1.666e-02 -1.170 0.2419
## categoryNon-BRI:s(day)9 -1.362e-02 1.715e-02 -0.794 0.4273
## categoryNon-BRI:s(day)10 6.027e-06 1.589e-02 0.000 0.9997
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 14:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0095363 0.0088222 1.081 0.280
## categoryNon-BRI 0.0047217 0.0098865 0.478 0.633
## s(day)1 0.0127398 0.0156247 0.815 0.415
## s(day)2 -0.0043494 0.0087633 -0.496 0.620
## s(day)3 0.0081963 0.0108506 0.755 0.450
## s(day)4 -0.0021642 0.0092129 -0.235 0.814
## s(day)5 0.0018277 0.0098355 0.186 0.853
## s(day)6 0.0039217 0.0102329 0.383 0.702
## s(day)7 0.0011748 0.0103562 0.113 0.910
## s(day)8 0.0093211 0.0104869 0.889 0.374
## s(day)9 -0.0018442 0.0108543 -0.170 0.865
## s(day)10 0.0027719 0.0102224 0.271 0.786
## categoryNon-BRI:s(day)1 -0.0133922 0.0175925 -0.761 0.447
## categoryNon-BRI:s(day)2 0.0086917 0.0101409 0.857 0.391
## categoryNon-BRI:s(day)3 -0.0110194 0.0122304 -0.901 0.368
## categoryNon-BRI:s(day)4 -0.0011611 0.0107890 -0.108 0.914
## categoryNon-BRI:s(day)5 -0.0005060 0.0112593 -0.045 0.964
## categoryNon-BRI:s(day)6 -0.0047410 0.0116389 -0.407 0.684
## categoryNon-BRI:s(day)7 -0.0035072 0.0122568 -0.286 0.775
## categoryNon-BRI:s(day)8 -0.0105569 0.0119278 -0.885 0.376
## categoryNon-BRI:s(day)9 0.0008403 0.0127526 0.066 0.947
## categoryNon-BRI:s(day)10 -0.0075563 0.0117878 -0.641 0.522
##
##
## Topic 15:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0221999 0.0099493 2.231 0.0257 *
## categoryNon-BRI 0.0059207 0.0111629 0.530 0.5958
## s(day)1 0.0198250 0.0165630 1.197 0.2313
## s(day)2 -0.0004811 0.0103987 -0.046 0.9631
## s(day)3 0.0081230 0.0121494 0.669 0.5038
## s(day)4 0.0074275 0.0104119 0.713 0.4756
## s(day)5 -0.0063380 0.0111090 -0.571 0.5683
## s(day)6 0.0190112 0.0112961 1.683 0.0924 .
## s(day)7 0.0003002 0.0118810 0.025 0.9798
## s(day)8 0.0119421 0.0116813 1.022 0.3066
## s(day)9 -0.0027802 0.0129680 -0.214 0.8302
## s(day)10 0.0146928 0.0114298 1.285 0.1986
## categoryNon-BRI:s(day)1 -0.0249760 0.0191641 -1.303 0.1925
## categoryNon-BRI:s(day)2 0.0068375 0.0116448 0.587 0.5571
## categoryNon-BRI:s(day)3 -0.0108488 0.0139012 -0.780 0.4351
## categoryNon-BRI:s(day)4 -0.0010357 0.0118145 -0.088 0.9301
## categoryNon-BRI:s(day)5 0.0011072 0.0126946 0.087 0.9305
## categoryNon-BRI:s(day)6 -0.0170834 0.0130502 -1.309 0.1905
## categoryNon-BRI:s(day)7 -0.0044814 0.0137423 -0.326 0.7443
## categoryNon-BRI:s(day)8 -0.0059085 0.0139956 -0.422 0.6729
## categoryNon-BRI:s(day)9 -0.0038055 0.0145561 -0.261 0.7938
## categoryNon-BRI:s(day)10 -0.0187650 0.0128904 -1.456 0.1455
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 16:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.042925 0.008290 5.178 2.25e-07 ***
## categoryNon-BRI -0.011266 0.009817 -1.148 0.2511
## s(day)1 -0.020461 0.014239 -1.437 0.1507
## s(day)2 -0.011945 0.009409 -1.270 0.2042
## s(day)3 -0.018904 0.009998 -1.891 0.0587 .
## s(day)4 -0.010015 0.009150 -1.094 0.2738
## s(day)5 -0.028932 0.009270 -3.121 0.0018 **
## s(day)6 -0.002766 0.009944 -0.278 0.7809
## s(day)7 -0.019687 0.009693 -2.031 0.0422 *
## s(day)8 -0.010585 0.010295 -1.028 0.3039
## s(day)9 -0.026794 0.010628 -2.521 0.0117 *
## s(day)10 -0.019135 0.009970 -1.919 0.0549 .
## categoryNon-BRI:s(day)1 0.017079 0.016458 1.038 0.2994
## categoryNon-BRI:s(day)2 0.006039 0.010814 0.558 0.5766
## categoryNon-BRI:s(day)3 0.019819 0.012156 1.630 0.1030
## categoryNon-BRI:s(day)4 0.003863 0.010606 0.364 0.7157
## categoryNon-BRI:s(day)5 0.024892 0.011160 2.231 0.0257 *
## categoryNon-BRI:s(day)6 -0.005112 0.011412 -0.448 0.6542
## categoryNon-BRI:s(day)7 0.015203 0.011646 1.305 0.1918
## categoryNon-BRI:s(day)8 0.001020 0.012110 0.084 0.9329
## categoryNon-BRI:s(day)9 0.028286 0.012615 2.242 0.0250 *
## categoryNon-BRI:s(day)10 0.012765 0.011750 1.086 0.2773
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 17:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0081565 0.0056659 1.440 0.1500
## categoryNon-BRI 0.0025298 0.0066177 0.382 0.7023
## s(day)1 0.0080874 0.0099096 0.816 0.4144
## s(day)2 -0.0016193 0.0062380 -0.260 0.7952
## s(day)3 0.0062162 0.0070709 0.879 0.3793
## s(day)4 0.0033015 0.0061880 0.534 0.5937
## s(day)5 0.0041799 0.0063145 0.662 0.5080
## s(day)6 0.0032496 0.0066323 0.490 0.6242
## s(day)7 0.0054330 0.0069253 0.785 0.4327
## s(day)8 -0.0007040 0.0069820 -0.101 0.9197
## s(day)9 0.0127078 0.0075100 1.692 0.0906 .
## s(day)10 -0.0017728 0.0067960 -0.261 0.7942
## categoryNon-BRI:s(day)1 -0.0030229 0.0118530 -0.255 0.7987
## categoryNon-BRI:s(day)2 -0.0006068 0.0072495 -0.084 0.9333
## categoryNon-BRI:s(day)3 -0.0011145 0.0083856 -0.133 0.8943
## categoryNon-BRI:s(day)4 -0.0057994 0.0072200 -0.803 0.4218
## categoryNon-BRI:s(day)5 -0.0013281 0.0076454 -0.174 0.8621
## categoryNon-BRI:s(day)6 -0.0015461 0.0076611 -0.202 0.8401
## categoryNon-BRI:s(day)7 -0.0054823 0.0083845 -0.654 0.5132
## categoryNon-BRI:s(day)8 0.0072279 0.0083754 0.863 0.3881
## categoryNon-BRI:s(day)9 -0.0187472 0.0088288 -2.123 0.0337 *
## categoryNon-BRI:s(day)10 0.0026123 0.0077974 0.335 0.7376
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 18:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0189680 0.0064833 2.926 0.00344 **
## categoryNon-BRI 0.0003168 0.0074497 0.043 0.96608
## s(day)1 0.0024751 0.0111779 0.221 0.82476
## s(day)2 -0.0068632 0.0068397 -1.003 0.31566
## s(day)3 0.0048402 0.0077245 0.627 0.53092
## s(day)4 -0.0022158 0.0069952 -0.317 0.75143
## s(day)5 -0.0032584 0.0071220 -0.458 0.64730
## s(day)6 0.0015746 0.0074336 0.212 0.83225
## s(day)7 -0.0031064 0.0076590 -0.406 0.68505
## s(day)8 0.0042522 0.0078348 0.543 0.58732
## s(day)9 -0.0041752 0.0078810 -0.530 0.59627
## s(day)10 -0.0057171 0.0077257 -0.740 0.45930
## categoryNon-BRI:s(day)1 -0.0078714 0.0127480 -0.617 0.53693
## categoryNon-BRI:s(day)2 0.0084523 0.0078625 1.075 0.28237
## categoryNon-BRI:s(day)3 -0.0050780 0.0091395 -0.556 0.57848
## categoryNon-BRI:s(day)4 0.0027653 0.0080812 0.342 0.73221
## categoryNon-BRI:s(day)5 0.0032102 0.0084429 0.380 0.70378
## categoryNon-BRI:s(day)6 -0.0007502 0.0084895 -0.088 0.92959
## categoryNon-BRI:s(day)7 -0.0001915 0.0090302 -0.021 0.98308
## categoryNon-BRI:s(day)8 -0.0036850 0.0091540 -0.403 0.68727
## categoryNon-BRI:s(day)9 0.0028204 0.0095113 0.297 0.76682
## categoryNon-BRI:s(day)10 0.0054862 0.0090918 0.603 0.54623
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 19:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.413e-02 9.063e-03 3.765 0.000167 ***
## categoryNon-BRI 1.056e-03 1.045e-02 0.101 0.919527
## s(day)1 9.057e-03 1.522e-02 0.595 0.551799
## s(day)2 5.110e-03 9.670e-03 0.528 0.597230
## s(day)3 7.741e-05 1.101e-02 0.007 0.994390
## s(day)4 4.404e-03 9.738e-03 0.452 0.651093
## s(day)5 3.041e-03 1.014e-02 0.300 0.764319
## s(day)6 6.846e-03 1.035e-02 0.661 0.508439
## s(day)7 -9.838e-04 1.041e-02 -0.095 0.924684
## s(day)8 3.989e-04 1.129e-02 0.035 0.971820
## s(day)9 1.247e-03 1.102e-02 0.113 0.909930
## s(day)10 -8.760e-04 1.077e-02 -0.081 0.935175
## categoryNon-BRI:s(day)1 6.168e-04 1.792e-02 0.034 0.972546
## categoryNon-BRI:s(day)2 -2.521e-03 1.109e-02 -0.227 0.820132
## categoryNon-BRI:s(day)3 3.843e-03 1.296e-02 0.297 0.766815
## categoryNon-BRI:s(day)4 8.662e-04 1.149e-02 0.075 0.939921
## categoryNon-BRI:s(day)5 -2.560e-03 1.176e-02 -0.218 0.827652
## categoryNon-BRI:s(day)6 -4.225e-03 1.228e-02 -0.344 0.730713
## categoryNon-BRI:s(day)7 9.058e-03 1.227e-02 0.738 0.460343
## categoryNon-BRI:s(day)8 -9.469e-04 1.314e-02 -0.072 0.942570
## categoryNon-BRI:s(day)9 -3.692e-04 1.361e-02 -0.027 0.978352
## categoryNon-BRI:s(day)10 6.720e-03 1.244e-02 0.540 0.589119
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 20:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0174833 0.0065170 2.683 0.00731 **
## categoryNon-BRI 0.0016038 0.0071899 0.223 0.82349
## s(day)1 -0.0003899 0.0112693 -0.035 0.97240
## s(day)2 0.0001062 0.0069640 0.015 0.98783
## s(day)3 -0.0040630 0.0078777 -0.516 0.60603
## s(day)4 0.0023387 0.0069150 0.338 0.73521
## s(day)5 -0.0040017 0.0073387 -0.545 0.58555
## s(day)6 0.0015842 0.0073345 0.216 0.82900
## s(day)7 -0.0002499 0.0076415 -0.033 0.97391
## s(day)8 0.0009631 0.0080066 0.120 0.90425
## s(day)9 0.0045040 0.0084862 0.531 0.59559
## s(day)10 -0.0073463 0.0076228 -0.964 0.33519
## categoryNon-BRI:s(day)1 -0.0021944 0.0127569 -0.172 0.86342
## categoryNon-BRI:s(day)2 -0.0044491 0.0078168 -0.569 0.56925
## categoryNon-BRI:s(day)3 0.0014696 0.0089344 0.164 0.86935
## categoryNon-BRI:s(day)4 -0.0034299 0.0080007 -0.429 0.66815
## categoryNon-BRI:s(day)5 0.0011513 0.0081575 0.141 0.88777
## categoryNon-BRI:s(day)6 -0.0015191 0.0083725 -0.181 0.85603
## categoryNon-BRI:s(day)7 -0.0014851 0.0086574 -0.172 0.86380
## categoryNon-BRI:s(day)8 -0.0039838 0.0092249 -0.432 0.66585
## categoryNon-BRI:s(day)9 -0.0052784 0.0098262 -0.537 0.59115
## categoryNon-BRI:s(day)10 0.0067004 0.0084491 0.793 0.42776
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 21:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.017986 0.010423 1.726 0.08443 .
## categoryNon-BRI 0.013458 0.011944 1.127 0.25985
## s(day)1 0.038715 0.017953 2.156 0.03105 *
## s(day)2 0.011621 0.011081 1.049 0.29427
## s(day)3 0.025245 0.012698 1.988 0.04681 *
## s(day)4 0.002365 0.011361 0.208 0.83513
## s(day)5 0.047162 0.011434 4.125 3.72e-05 ***
## s(day)6 -0.006100 0.011570 -0.527 0.59803
## s(day)7 0.039236 0.012405 3.163 0.00156 **
## s(day)8 0.010940 0.011911 0.918 0.35838
## s(day)9 0.026495 0.013821 1.917 0.05524 .
## s(day)10 0.024643 0.012075 2.041 0.04127 *
## categoryNon-BRI:s(day)1 -0.027267 0.020439 -1.334 0.18219
## categoryNon-BRI:s(day)2 -0.014337 0.012755 -1.124 0.26102
## categoryNon-BRI:s(day)3 -0.023488 0.014681 -1.600 0.10963
## categoryNon-BRI:s(day)4 0.005958 0.013495 0.442 0.65885
## categoryNon-BRI:s(day)5 -0.038976 0.013378 -2.913 0.00358 **
## categoryNon-BRI:s(day)6 0.007112 0.013722 0.518 0.60426
## categoryNon-BRI:s(day)7 -0.033325 0.014407 -2.313 0.02073 *
## categoryNon-BRI:s(day)8 -0.008113 0.014202 -0.571 0.56785
## categoryNon-BRI:s(day)9 -0.019521 0.015771 -1.238 0.21582
## categoryNon-BRI:s(day)10 -0.021203 0.014028 -1.511 0.13067
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 22:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0381400 0.0108168 3.526 0.000422 ***
## categoryNon-BRI -0.0003064 0.0122273 -0.025 0.980007
## s(day)1 0.0089367 0.0180108 0.496 0.619765
## s(day)2 0.0068894 0.0118412 0.582 0.560691
## s(day)3 -0.0014667 0.0126216 -0.116 0.907490
## s(day)4 0.0209078 0.0122608 1.705 0.088151 .
## s(day)5 -0.0070768 0.0114831 -0.616 0.537712
## s(day)6 0.0134373 0.0125340 1.072 0.283698
## s(day)7 -0.0037562 0.0129129 -0.291 0.771139
## s(day)8 0.0151373 0.0127000 1.192 0.233301
## s(day)9 0.0073067 0.0142232 0.514 0.607455
## s(day)10 0.0010208 0.0124277 0.082 0.934538
## categoryNon-BRI:s(day)1 0.0043683 0.0208340 0.210 0.833925
## categoryNon-BRI:s(day)2 -0.0000998 0.0133409 -0.007 0.994031
## categoryNon-BRI:s(day)3 0.0056645 0.0146927 0.386 0.699843
## categoryNon-BRI:s(day)4 -0.0082711 0.0138843 -0.596 0.551369
## categoryNon-BRI:s(day)5 0.0109429 0.0133812 0.818 0.413486
## categoryNon-BRI:s(day)6 -0.0015158 0.0149256 -0.102 0.919108
## categoryNon-BRI:s(day)7 0.0121026 0.0146418 0.827 0.408479
## categoryNon-BRI:s(day)8 -0.0143208 0.0155810 -0.919 0.358035
## categoryNon-BRI:s(day)9 0.0032840 0.0166821 0.197 0.843941
## categoryNon-BRI:s(day)10 0.0077719 0.0143229 0.543 0.587394
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 23:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.035859 0.005792 6.192 6.00e-10 ***
## categoryNon-BRI -0.029807 0.006539 -4.559 5.16e-06 ***
## s(day)1 -0.031625 0.009903 -3.194 0.001406 **
## s(day)2 -0.025205 0.006358 -3.964 7.37e-05 ***
## s(day)3 -0.026011 0.006958 -3.739 0.000185 ***
## s(day)4 -0.023812 0.006297 -3.782 0.000156 ***
## s(day)5 -0.026971 0.006304 -4.279 1.88e-05 ***
## s(day)6 -0.021008 0.006735 -3.119 0.001815 **
## s(day)7 -0.026886 0.006937 -3.875 0.000107 ***
## s(day)8 -0.024434 0.007215 -3.387 0.000708 ***
## s(day)9 -0.018632 0.007360 -2.531 0.011366 *
## s(day)10 -0.028798 0.006852 -4.203 2.64e-05 ***
## categoryNon-BRI:s(day)1 0.040058 0.011584 3.458 0.000545 ***
## categoryNon-BRI:s(day)2 0.023940 0.007328 3.267 0.001089 **
## categoryNon-BRI:s(day)3 0.036114 0.007945 4.545 5.50e-06 ***
## categoryNon-BRI:s(day)4 0.028252 0.007144 3.955 7.67e-05 ***
## categoryNon-BRI:s(day)5 0.034687 0.007148 4.853 1.22e-06 ***
## categoryNon-BRI:s(day)6 0.026933 0.007643 3.524 0.000426 ***
## categoryNon-BRI:s(day)7 0.035112 0.008157 4.305 1.68e-05 ***
## categoryNon-BRI:s(day)8 0.028570 0.008412 3.396 0.000683 ***
## categoryNon-BRI:s(day)9 0.025743 0.008723 2.951 0.003169 **
## categoryNon-BRI:s(day)10 0.034424 0.007874 4.372 1.23e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 24:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.443e-02 1.162e-02 2.963 0.00305 **
## categoryNon-BRI -3.843e-05 1.315e-02 -0.003 0.99767
## s(day)1 1.782e-02 1.987e-02 0.897 0.36964
## s(day)2 7.064e-03 1.234e-02 0.573 0.56696
## s(day)3 3.139e-03 1.360e-02 0.231 0.81753
## s(day)4 3.636e-03 1.280e-02 0.284 0.77637
## s(day)5 -1.320e-02 1.245e-02 -1.060 0.28910
## s(day)6 1.085e-02 1.346e-02 0.806 0.42022
## s(day)7 4.043e-04 1.342e-02 0.030 0.97596
## s(day)8 -1.976e-03 1.448e-02 -0.137 0.89141
## s(day)9 2.797e-03 1.449e-02 0.193 0.84689
## s(day)10 -3.497e-03 1.351e-02 -0.259 0.79581
## categoryNon-BRI:s(day)1 -2.163e-02 2.265e-02 -0.955 0.33953
## categoryNon-BRI:s(day)2 3.109e-03 1.417e-02 0.219 0.82631
## categoryNon-BRI:s(day)3 -7.058e-03 1.556e-02 -0.454 0.65001
## categoryNon-BRI:s(day)4 1.840e-03 1.473e-02 0.125 0.90059
## categoryNon-BRI:s(day)5 1.120e-02 1.443e-02 0.777 0.43741
## categoryNon-BRI:s(day)6 -4.041e-03 1.532e-02 -0.264 0.79194
## categoryNon-BRI:s(day)7 -4.071e-03 1.531e-02 -0.266 0.79027
## categoryNon-BRI:s(day)8 7.510e-03 1.733e-02 0.433 0.66479
## categoryNon-BRI:s(day)9 -4.788e-03 1.678e-02 -0.285 0.77537
## categoryNon-BRI:s(day)10 7.447e-04 1.540e-02 0.048 0.96144
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 25:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0510405 0.0116396 4.385 1.16e-05 ***
## categoryNon-BRI -0.0083000 0.0133489 -0.622 0.534
## s(day)1 -0.0187386 0.0200659 -0.934 0.350
## s(day)2 0.0061499 0.0118176 0.520 0.603
## s(day)3 -0.0145161 0.0140389 -1.034 0.301
## s(day)4 -0.0051051 0.0122429 -0.417 0.677
## s(day)5 -0.0193648 0.0131700 -1.470 0.141
## s(day)6 -0.0046120 0.0132793 -0.347 0.728
## s(day)7 -0.0095536 0.0135527 -0.705 0.481
## s(day)8 -0.0167985 0.0145663 -1.153 0.249
## s(day)9 -0.0009412 0.0145988 -0.064 0.949
## s(day)10 -0.0222340 0.0138134 -1.610 0.107
## categoryNon-BRI:s(day)1 0.0221793 0.0229415 0.967 0.334
## categoryNon-BRI:s(day)2 -0.0129682 0.0139932 -0.927 0.354
## categoryNon-BRI:s(day)3 0.0182597 0.0163519 1.117 0.264
## categoryNon-BRI:s(day)4 0.0008506 0.0144839 0.059 0.953
## categoryNon-BRI:s(day)5 0.0121034 0.0149699 0.809 0.419
## categoryNon-BRI:s(day)6 0.0036410 0.0155973 0.233 0.815
## categoryNon-BRI:s(day)7 0.0016736 0.0158090 0.106 0.916
## categoryNon-BRI:s(day)8 0.0211577 0.0164930 1.283 0.200
## categoryNon-BRI:s(day)9 -0.0015091 0.0177957 -0.085 0.932
## categoryNon-BRI:s(day)10 0.0184677 0.0157869 1.170 0.242
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 26:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0155153 0.0051286 3.025 0.00249 **
## categoryNon-BRI 0.0004240 0.0058990 0.072 0.94270
## s(day)1 -0.0047174 0.0090621 -0.521 0.60267
## s(day)2 -0.0051014 0.0053852 -0.947 0.34349
## s(day)3 -0.0044830 0.0062571 -0.716 0.47371
## s(day)4 -0.0002345 0.0055225 -0.042 0.96614
## s(day)5 -0.0088582 0.0057537 -1.540 0.12367
## s(day)6 -0.0007156 0.0059984 -0.119 0.90505
## s(day)7 -0.0069999 0.0063246 -1.107 0.26840
## s(day)8 -0.0024466 0.0062160 -0.394 0.69388
## s(day)9 -0.0057186 0.0066479 -0.860 0.38968
## s(day)10 -0.0057352 0.0059844 -0.958 0.33789
## categoryNon-BRI:s(day)1 -0.0052523 0.0105172 -0.499 0.61750
## categoryNon-BRI:s(day)2 0.0056304 0.0064954 0.867 0.38604
## categoryNon-BRI:s(day)3 -0.0034929 0.0073557 -0.475 0.63489
## categoryNon-BRI:s(day)4 -0.0009849 0.0065303 -0.151 0.88012
## categoryNon-BRI:s(day)5 0.0026973 0.0067709 0.398 0.69036
## categoryNon-BRI:s(day)6 -0.0011845 0.0070237 -0.169 0.86607
## categoryNon-BRI:s(day)7 0.0004950 0.0072998 0.068 0.94594
## categoryNon-BRI:s(day)8 -0.0008980 0.0073970 -0.121 0.90337
## categoryNon-BRI:s(day)9 -0.0011313 0.0075426 -0.150 0.88078
## categoryNon-BRI:s(day)10 0.0028041 0.0070084 0.400 0.68908
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 27:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.007636 0.007771 0.983 0.3258
## categoryNon-BRI 0.019298 0.009054 2.131 0.0331 *
## s(day)1 0.022634 0.013237 1.710 0.0873 .
## s(day)2 0.014540 0.008606 1.690 0.0911 .
## s(day)3 0.021359 0.009525 2.242 0.0249 *
## s(day)4 0.019376 0.008460 2.290 0.0220 *
## s(day)5 0.011231 0.008788 1.278 0.2013
## s(day)6 0.019289 0.008886 2.171 0.0300 *
## s(day)7 0.022103 0.009678 2.284 0.0224 *
## s(day)8 0.013083 0.009593 1.364 0.1726
## s(day)9 0.019903 0.010261 1.940 0.0524 .
## s(day)10 0.007076 0.009408 0.752 0.4520
## categoryNon-BRI:s(day)1 -0.017399 0.015430 -1.128 0.2595
## categoryNon-BRI:s(day)2 -0.020279 0.010052 -2.017 0.0437 *
## categoryNon-BRI:s(day)3 -0.022196 0.011101 -1.999 0.0456 *
## categoryNon-BRI:s(day)4 -0.020506 0.010094 -2.032 0.0422 *
## categoryNon-BRI:s(day)5 -0.009338 0.010280 -0.908 0.3637
## categoryNon-BRI:s(day)6 -0.020875 0.010589 -1.971 0.0487 *
## categoryNon-BRI:s(day)7 -0.022113 0.011206 -1.973 0.0485 *
## categoryNon-BRI:s(day)8 -0.014518 0.011432 -1.270 0.2041
## categoryNon-BRI:s(day)9 -0.016079 0.012400 -1.297 0.1947
## categoryNon-BRI:s(day)10 -0.008198 0.011002 -0.745 0.4562
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 28:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.493e-02 6.099e-03 4.087 4.38e-05 ***
## categoryNon-BRI -4.791e-04 6.974e-03 -0.069 0.9452
## s(day)1 -1.014e-02 1.044e-02 -0.971 0.3315
## s(day)2 -8.720e-04 6.522e-03 -0.134 0.8936
## s(day)3 -9.851e-03 7.452e-03 -1.322 0.1862
## s(day)4 -6.970e-03 6.742e-03 -1.034 0.3012
## s(day)5 -9.191e-03 6.729e-03 -1.366 0.1720
## s(day)6 -4.786e-05 7.301e-03 -0.007 0.9948
## s(day)7 -1.713e-02 7.000e-03 -2.446 0.0144 *
## s(day)8 -1.738e-03 7.451e-03 -0.233 0.8156
## s(day)9 -4.692e-03 8.101e-03 -0.579 0.5624
## s(day)10 -1.127e-02 7.129e-03 -1.581 0.1140
## categoryNon-BRI:s(day)1 -3.538e-03 1.191e-02 -0.297 0.7664
## categoryNon-BRI:s(day)2 -1.178e-03 7.557e-03 -0.156 0.8761
## categoryNon-BRI:s(day)3 -4.255e-04 8.465e-03 -0.050 0.9599
## categoryNon-BRI:s(day)4 4.604e-03 7.689e-03 0.599 0.5493
## categoryNon-BRI:s(day)5 1.098e-03 7.997e-03 0.137 0.8908
## categoryNon-BRI:s(day)6 -4.843e-03 8.295e-03 -0.584 0.5593
## categoryNon-BRI:s(day)7 7.764e-03 8.083e-03 0.961 0.3368
## categoryNon-BRI:s(day)8 -4.923e-03 8.965e-03 -0.549 0.5829
## categoryNon-BRI:s(day)9 -4.594e-03 9.293e-03 -0.494 0.6211
## categoryNon-BRI:s(day)10 3.664e-03 8.354e-03 0.439 0.6609
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 29:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.204e-03 4.235e-03 0.284 0.7761
## categoryNon-BRI 6.098e-03 4.684e-03 1.302 0.1929
## s(day)1 5.212e-03 7.151e-03 0.729 0.4661
## s(day)2 4.743e-03 4.516e-03 1.050 0.2936
## s(day)3 5.654e-03 5.057e-03 1.118 0.2636
## s(day)4 5.046e-03 4.554e-03 1.108 0.2678
## s(day)5 2.716e-03 4.775e-03 0.569 0.5696
## s(day)6 7.795e-03 4.710e-03 1.655 0.0979 .
## s(day)7 -3.823e-05 5.073e-03 -0.008 0.9940
## s(day)8 1.308e-02 5.191e-03 2.519 0.0118 *
## s(day)9 1.208e-03 5.382e-03 0.224 0.8224
## s(day)10 8.599e-03 4.782e-03 1.798 0.0722 .
## categoryNon-BRI:s(day)1 -8.517e-03 8.066e-03 -1.056 0.2910
## categoryNon-BRI:s(day)2 -3.957e-03 5.123e-03 -0.772 0.4399
## categoryNon-BRI:s(day)3 -8.300e-03 5.697e-03 -1.457 0.1451
## categoryNon-BRI:s(day)4 -1.290e-03 5.080e-03 -0.254 0.7995
## categoryNon-BRI:s(day)5 -5.280e-03 5.456e-03 -0.968 0.3332
## categoryNon-BRI:s(day)6 -8.516e-03 5.326e-03 -1.599 0.1099
## categoryNon-BRI:s(day)7 -6.868e-04 5.764e-03 -0.119 0.9052
## categoryNon-BRI:s(day)8 -1.421e-02 5.915e-03 -2.402 0.0163 *
## categoryNon-BRI:s(day)9 -2.011e-03 6.051e-03 -0.332 0.7397
## categoryNon-BRI:s(day)10 -1.173e-02 5.499e-03 -2.133 0.0329 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 30:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.039953 0.007977 5.009 5.5e-07 ***
## categoryNon-BRI -0.019775 0.009311 -2.124 0.03368 *
## s(day)1 -0.025899 0.013999 -1.850 0.06431 .
## s(day)2 -0.013397 0.008304 -1.613 0.10668
## s(day)3 -0.010572 0.009889 -1.069 0.28503
## s(day)4 -0.018232 0.008379 -2.176 0.02957 *
## s(day)5 -0.013400 0.008910 -1.504 0.13262
## s(day)6 -0.019739 0.009453 -2.088 0.03679 *
## s(day)7 -0.003730 0.009566 -0.390 0.69662
## s(day)8 -0.017228 0.010033 -1.717 0.08595 .
## s(day)9 -0.015174 0.010564 -1.436 0.15090
## s(day)10 -0.010270 0.009173 -1.120 0.26287
## categoryNon-BRI:s(day)1 0.040694 0.016673 2.441 0.01466 *
## categoryNon-BRI:s(day)2 0.016966 0.009603 1.767 0.07728 .
## categoryNon-BRI:s(day)3 0.022012 0.011781 1.868 0.06170 .
## categoryNon-BRI:s(day)4 0.026419 0.009820 2.690 0.00714 **
## categoryNon-BRI:s(day)5 0.016281 0.010775 1.511 0.13082
## categoryNon-BRI:s(day)6 0.031105 0.011171 2.785 0.00536 **
## categoryNon-BRI:s(day)7 0.012024 0.011240 1.070 0.28472
## categoryNon-BRI:s(day)8 0.023872 0.011828 2.018 0.04358 *
## categoryNon-BRI:s(day)9 0.022033 0.012460 1.768 0.07702 .
## categoryNon-BRI:s(day)10 0.018766 0.010833 1.732 0.08323 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 31:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.043792 0.009510 4.605 4.14e-06 ***
## categoryNon-BRI -0.003819 0.010860 -0.352 0.7251
## s(day)1 -0.014292 0.016385 -0.872 0.3831
## s(day)2 -0.008011 0.010579 -0.757 0.4489
## s(day)3 0.005235 0.011675 0.448 0.6539
## s(day)4 -0.003001 0.010435 -0.288 0.7737
## s(day)5 -0.016479 0.010588 -1.556 0.1196
## s(day)6 0.009018 0.011165 0.808 0.4193
## s(day)7 -0.009118 0.010946 -0.833 0.4048
## s(day)8 0.013612 0.011789 1.155 0.2483
## s(day)9 -0.020784 0.011773 -1.765 0.0775 .
## s(day)10 -0.006920 0.011475 -0.603 0.5465
## categoryNon-BRI:s(day)1 0.011569 0.018750 0.617 0.5372
## categoryNon-BRI:s(day)2 0.012911 0.012303 1.049 0.2940
## categoryNon-BRI:s(day)3 -0.005603 0.013068 -0.429 0.6681
## categoryNon-BRI:s(day)4 -0.001830 0.012117 -0.151 0.8799
## categoryNon-BRI:s(day)5 0.015993 0.012224 1.308 0.1908
## categoryNon-BRI:s(day)6 -0.004891 0.013071 -0.374 0.7083
## categoryNon-BRI:s(day)7 0.005975 0.012544 0.476 0.6338
## categoryNon-BRI:s(day)8 -0.007362 0.014274 -0.516 0.6061
## categoryNon-BRI:s(day)9 0.015716 0.013893 1.131 0.2580
## categoryNon-BRI:s(day)10 0.008577 0.013255 0.647 0.5176
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 32:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0552344 0.0140478 3.932 8.44e-05 ***
## categoryNon-BRI 0.0090016 0.0163341 0.551 0.5816
## s(day)1 0.0009246 0.0249057 0.037 0.9704
## s(day)2 0.0119618 0.0146544 0.816 0.4144
## s(day)3 0.0002237 0.0169375 0.013 0.9895
## s(day)4 0.0129883 0.0152605 0.851 0.3947
## s(day)5 -0.0141863 0.0158163 -0.897 0.3698
## s(day)6 0.0147025 0.0155659 0.945 0.3449
## s(day)7 -0.0122942 0.0167785 -0.733 0.4637
## s(day)8 0.0298890 0.0174924 1.709 0.0875 .
## s(day)9 -0.0119071 0.0185256 -0.643 0.5204
## s(day)10 0.0019406 0.0161592 0.120 0.9044
## categoryNon-BRI:s(day)1 -0.0087019 0.0296450 -0.294 0.7691
## categoryNon-BRI:s(day)2 -0.0103108 0.0176381 -0.585 0.5588
## categoryNon-BRI:s(day)3 -0.0103715 0.0200431 -0.517 0.6048
## categoryNon-BRI:s(day)4 -0.0076974 0.0182541 -0.422 0.6733
## categoryNon-BRI:s(day)5 -0.0010040 0.0186224 -0.054 0.9570
## categoryNon-BRI:s(day)6 -0.0064338 0.0184953 -0.348 0.7279
## categoryNon-BRI:s(day)7 -0.0105967 0.0199299 -0.532 0.5949
## categoryNon-BRI:s(day)8 -0.0194873 0.0208151 -0.936 0.3492
## categoryNon-BRI:s(day)9 0.0021133 0.0218968 0.097 0.9231
## categoryNon-BRI:s(day)10 -0.0117639 0.0193336 -0.608 0.5429
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 33:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0241112 0.0071805 3.358 0.000786 ***
## categoryNon-BRI 0.0051712 0.0080665 0.641 0.521481
## s(day)1 0.0053292 0.0121659 0.438 0.661356
## s(day)2 0.0024569 0.0077836 0.316 0.752272
## s(day)3 0.0028163 0.0086577 0.325 0.744961
## s(day)4 0.0090608 0.0076311 1.187 0.235094
## s(day)5 0.0009635 0.0081016 0.119 0.905339
## s(day)6 0.0034677 0.0079292 0.437 0.661874
## s(day)7 0.0077970 0.0085384 0.913 0.361154
## s(day)8 0.0010036 0.0089625 0.112 0.910837
## s(day)9 0.0083374 0.0092859 0.898 0.369270
## s(day)10 0.0006393 0.0082651 0.077 0.938348
## categoryNon-BRI:s(day)1 -0.0040955 0.0138465 -0.296 0.767399
## categoryNon-BRI:s(day)2 -0.0082947 0.0088440 -0.938 0.348307
## categoryNon-BRI:s(day)3 0.0014539 0.0100885 0.144 0.885409
## categoryNon-BRI:s(day)4 -0.0104718 0.0087135 -1.202 0.229446
## categoryNon-BRI:s(day)5 -0.0017849 0.0092878 -0.192 0.847605
## categoryNon-BRI:s(day)6 -0.0035145 0.0092027 -0.382 0.702541
## categoryNon-BRI:s(day)7 -0.0096791 0.0097175 -0.996 0.319228
## categoryNon-BRI:s(day)8 -0.0014213 0.0101978 -0.139 0.889154
## categoryNon-BRI:s(day)9 -0.0088633 0.0107602 -0.824 0.410108
## categoryNon-BRI:s(day)10 0.0004943 0.0093886 0.053 0.958009
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 34:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0246516 0.0097316 2.533 0.0113 *
## categoryNon-BRI -0.0017003 0.0111243 -0.153 0.8785
## s(day)1 0.0091811 0.0163384 0.562 0.5742
## s(day)2 -0.0086308 0.0100778 -0.856 0.3918
## s(day)3 0.0001256 0.0117482 0.011 0.9915
## s(day)4 0.0097236 0.0102362 0.950 0.3422
## s(day)5 -0.0146389 0.0110131 -1.329 0.1838
## s(day)6 0.0104887 0.0106741 0.983 0.3258
## s(day)7 -0.0060047 0.0110832 -0.542 0.5880
## s(day)8 0.0049533 0.0116578 0.425 0.6709
## s(day)9 0.0038411 0.0120816 0.318 0.7505
## s(day)10 -0.0093100 0.0112177 -0.830 0.4066
## categoryNon-BRI:s(day)1 -0.0092486 0.0189581 -0.488 0.6257
## categoryNon-BRI:s(day)2 0.0134786 0.0117235 1.150 0.2503
## categoryNon-BRI:s(day)3 0.0060668 0.0133983 0.453 0.6507
## categoryNon-BRI:s(day)4 -0.0114803 0.0119651 -0.959 0.3373
## categoryNon-BRI:s(day)5 0.0187269 0.0128076 1.462 0.1437
## categoryNon-BRI:s(day)6 -0.0066420 0.0125025 -0.531 0.5952
## categoryNon-BRI:s(day)7 0.0075689 0.0128622 0.588 0.5562
## categoryNon-BRI:s(day)8 0.0023440 0.0137467 0.171 0.8646
## categoryNon-BRI:s(day)9 -0.0085320 0.0144775 -0.589 0.5556
## categoryNon-BRI:s(day)10 0.0151793 0.0128440 1.182 0.2373
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 35:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0009020 0.0017508 0.515 0.606
## categoryNon-BRI 0.0010443 0.0020049 0.521 0.602
## s(day)1 -0.0005916 0.0030500 -0.194 0.846
## s(day)2 0.0020625 0.0018657 1.105 0.269
## s(day)3 -0.0003009 0.0020991 -0.143 0.886
## s(day)4 0.0017270 0.0018733 0.922 0.357
## s(day)5 0.0008808 0.0019156 0.460 0.646
## s(day)6 0.0008224 0.0020466 0.402 0.688
## s(day)7 0.0011275 0.0020221 0.558 0.577
## s(day)8 0.0019923 0.0020891 0.954 0.340
## s(day)9 -0.0004057 0.0022873 -0.177 0.859
## s(day)10 0.0017329 0.0020034 0.865 0.387
## categoryNon-BRI:s(day)1 0.0003356 0.0035074 0.096 0.924
## categoryNon-BRI:s(day)2 -0.0018322 0.0021374 -0.857 0.391
## categoryNon-BRI:s(day)3 0.0003313 0.0024590 0.135 0.893
## categoryNon-BRI:s(day)4 -0.0016301 0.0021871 -0.745 0.456
## categoryNon-BRI:s(day)5 -0.0004589 0.0022277 -0.206 0.837
## categoryNon-BRI:s(day)6 -0.0017624 0.0023684 -0.744 0.457
## categoryNon-BRI:s(day)7 0.0002935 0.0023648 0.124 0.901
## categoryNon-BRI:s(day)8 -0.0024667 0.0023909 -1.032 0.302
## categoryNon-BRI:s(day)9 0.0005983 0.0026780 0.223 0.823
## categoryNon-BRI:s(day)10 -0.0015096 0.0023480 -0.643 0.520
##
##
## Topic 36:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0048337 0.0036331 1.330 0.183
## categoryNon-BRI 0.0033506 0.0041028 0.817 0.414
## s(day)1 0.0028740 0.0063210 0.455 0.649
## s(day)2 -0.0004756 0.0039143 -0.122 0.903
## s(day)3 0.0033942 0.0046043 0.737 0.461
## s(day)4 0.0023076 0.0039067 0.591 0.555
## s(day)5 0.0004970 0.0040711 0.122 0.903
## s(day)6 0.0052430 0.0042144 1.244 0.213
## s(day)7 -0.0015378 0.0043881 -0.350 0.726
## s(day)8 0.0045399 0.0042167 1.077 0.282
## s(day)9 -0.0026636 0.0049773 -0.535 0.593
## s(day)10 0.0050057 0.0042026 1.191 0.234
## categoryNon-BRI:s(day)1 -0.0019705 0.0073524 -0.268 0.789
## categoryNon-BRI:s(day)2 -0.0021864 0.0045687 -0.479 0.632
## categoryNon-BRI:s(day)3 -0.0039883 0.0052992 -0.753 0.452
## categoryNon-BRI:s(day)4 -0.0021665 0.0044282 -0.489 0.625
## categoryNon-BRI:s(day)5 -0.0013694 0.0048367 -0.283 0.777
## categoryNon-BRI:s(day)6 -0.0064456 0.0048349 -1.333 0.182
## categoryNon-BRI:s(day)7 0.0013650 0.0051696 0.264 0.792
## categoryNon-BRI:s(day)8 -0.0080513 0.0050113 -1.607 0.108
## categoryNon-BRI:s(day)9 0.0043408 0.0056654 0.766 0.444
## categoryNon-BRI:s(day)10 -0.0062837 0.0048393 -1.298 0.194
##
##
## Topic 37:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.076665 0.010152 7.552 4.36e-14 ***
## categoryNon-BRI -0.018969 0.011799 -1.608 0.10791
## s(day)1 -0.041471 0.017338 -2.392 0.01676 *
## s(day)2 -0.007602 0.010903 -0.697 0.48564
## s(day)3 -0.033715 0.012433 -2.712 0.00669 **
## s(day)4 -0.024996 0.010686 -2.339 0.01933 *
## s(day)5 -0.031097 0.011653 -2.668 0.00762 **
## s(day)6 -0.020878 0.010926 -1.911 0.05603 .
## s(day)7 -0.032045 0.012375 -2.589 0.00962 **
## s(day)8 -0.025371 0.012219 -2.076 0.03786 *
## s(day)9 -0.025228 0.012898 -1.956 0.05048 .
## s(day)10 -0.028700 0.011477 -2.501 0.01240 *
## categoryNon-BRI:s(day)1 0.031251 0.020101 1.555 0.12002
## categoryNon-BRI:s(day)2 0.009026 0.012676 0.712 0.47647
## categoryNon-BRI:s(day)3 0.024187 0.014557 1.662 0.09661 .
## categoryNon-BRI:s(day)4 0.024039 0.012954 1.856 0.06351 .
## categoryNon-BRI:s(day)5 0.018693 0.013343 1.401 0.16123
## categoryNon-BRI:s(day)6 0.022790 0.012888 1.768 0.07701 .
## categoryNon-BRI:s(day)7 0.019023 0.014425 1.319 0.18728
## categoryNon-BRI:s(day)8 0.032229 0.014476 2.226 0.02600 *
## categoryNon-BRI:s(day)9 0.011617 0.015184 0.765 0.44424
## categoryNon-BRI:s(day)10 0.024102 0.013420 1.796 0.07252 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 38:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0216140 0.0093166 2.320 0.0203 *
## categoryNon-BRI -0.0004306 0.0107254 -0.040 0.9680
## s(day)1 -0.0127707 0.0155145 -0.823 0.4104
## s(day)2 -0.0046786 0.0097459 -0.480 0.6312
## s(day)3 -0.0026270 0.0112394 -0.234 0.8152
## s(day)4 -0.0016477 0.0098698 -0.167 0.8674
## s(day)5 -0.0132917 0.0102027 -1.303 0.1927
## s(day)6 0.0056294 0.0106853 0.527 0.5983
## s(day)7 -0.0119932 0.0108319 -1.107 0.2682
## s(day)8 -0.0020832 0.0111237 -0.187 0.8514
## s(day)9 -0.0022813 0.0119151 -0.191 0.8482
## s(day)10 -0.0162044 0.0104297 -1.554 0.1203
## categoryNon-BRI:s(day)1 -0.0007367 0.0181620 -0.041 0.9676
## categoryNon-BRI:s(day)2 0.0040061 0.0113150 0.354 0.7233
## categoryNon-BRI:s(day)3 -0.0016473 0.0131718 -0.125 0.9005
## categoryNon-BRI:s(day)4 -0.0017552 0.0114813 -0.153 0.8785
## categoryNon-BRI:s(day)5 0.0109484 0.0121244 0.903 0.3665
## categoryNon-BRI:s(day)6 -0.0112425 0.0123417 -0.911 0.3623
## categoryNon-BRI:s(day)7 0.0091029 0.0127178 0.716 0.4741
## categoryNon-BRI:s(day)8 -0.0057202 0.0129258 -0.443 0.6581
## categoryNon-BRI:s(day)9 0.0033422 0.0140666 0.238 0.8122
## categoryNon-BRI:s(day)10 0.0025743 0.0122878 0.210 0.8341
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 39:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0154432 0.0065824 2.346 0.019 *
## categoryNon-BRI 0.0051062 0.0075267 0.678 0.498
## s(day)1 0.0026077 0.0107826 0.242 0.809
## s(day)2 0.0021328 0.0069123 0.309 0.758
## s(day)3 0.0060839 0.0078447 0.776 0.438
## s(day)4 -0.0017752 0.0070278 -0.253 0.801
## s(day)5 0.0016777 0.0070752 0.237 0.813
## s(day)6 0.0028443 0.0075234 0.378 0.705
## s(day)7 -0.0019483 0.0075237 -0.259 0.796
## s(day)8 0.0049372 0.0079295 0.623 0.534
## s(day)9 -0.0045576 0.0084973 -0.536 0.592
## s(day)10 0.0013174 0.0074212 0.178 0.859
## categoryNon-BRI:s(day)1 -0.0110516 0.0124324 -0.889 0.374
## categoryNon-BRI:s(day)2 -0.0019174 0.0082355 -0.233 0.816
## categoryNon-BRI:s(day)3 -0.0106311 0.0089553 -1.187 0.235
## categoryNon-BRI:s(day)4 0.0001468 0.0081374 0.018 0.986
## categoryNon-BRI:s(day)5 -0.0070031 0.0083959 -0.834 0.404
## categoryNon-BRI:s(day)6 -0.0072965 0.0084530 -0.863 0.388
## categoryNon-BRI:s(day)7 0.0005080 0.0088462 0.057 0.954
## categoryNon-BRI:s(day)8 -0.0073087 0.0090882 -0.804 0.421
## categoryNon-BRI:s(day)9 0.0008319 0.0098177 0.085 0.932
## categoryNon-BRI:s(day)10 -0.0052621 0.0087732 -0.600 0.549
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Topic 40:
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.243e-03 4.532e-03 1.819 0.0690 .
## categoryNon-BRI 4.034e-03 5.231e-03 0.771 0.4406
## s(day)1 6.002e-03 7.941e-03 0.756 0.4498
## s(day)2 1.808e-03 4.901e-03 0.369 0.7123
## s(day)3 2.566e-03 5.498e-03 0.467 0.6407
## s(day)4 8.593e-04 4.984e-03 0.172 0.8631
## s(day)5 -8.816e-05 5.083e-03 -0.017 0.9862
## s(day)6 1.887e-03 5.164e-03 0.365 0.7148
## s(day)7 5.116e-03 5.409e-03 0.946 0.3443
## s(day)8 -1.850e-03 5.689e-03 -0.325 0.7451
## s(day)9 7.307e-03 5.673e-03 1.288 0.1977
## s(day)10 2.673e-04 5.220e-03 0.051 0.9592
## categoryNon-BRI:s(day)1 -5.296e-03 9.231e-03 -0.574 0.5662
## categoryNon-BRI:s(day)2 -6.452e-03 5.778e-03 -1.117 0.2642
## categoryNon-BRI:s(day)3 -2.478e-03 6.416e-03 -0.386 0.6993
## categoryNon-BRI:s(day)4 -3.606e-03 5.909e-03 -0.610 0.5417
## categoryNon-BRI:s(day)5 -2.536e-03 6.015e-03 -0.422 0.6733
## categoryNon-BRI:s(day)6 -7.184e-04 6.078e-03 -0.118 0.9059
## categoryNon-BRI:s(day)7 -9.695e-03 6.435e-03 -1.507 0.1319
## categoryNon-BRI:s(day)8 5.178e-03 6.760e-03 0.766 0.4437
## categoryNon-BRI:s(day)9 -1.201e-02 6.898e-03 -1.741 0.0817 .
## categoryNon-BRI:s(day)10 -2.046e-04 6.110e-03 -0.033 0.9733
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Topic prevalence is contrasted for two groups:
plot(prep, covariate = "category", topics = c(11, 15, 7, 24), model = topic_models_40 , method = "difference", cov.value1 = "BRI", cov.value2 = "Non-BRI", xlab = "Non-BRI BRI", main = "Effect of Entry to BRI", xlim = c(-0.07, 0.07), labeltype = "custom", custom.labels = c("Peng Shuai", "North Korea", "Space Tech", "Taiwan"))