install.packages(\"gtsummary\")\nlibrary(gtsummary)<\/code><\/pre>\n\n\n\n
Dados<\/h2>\n\n\n\n
AVC %>% DT::datatable()<\/code><\/pre>\n\n\n\n
Show 10 entries<\/p>\n\n\n\n
<\/th>
ID<\/th>
Idade<\/th>
Sexo<\/th>
Altura<\/th>
Peso<\/th>
IMC<\/th>
Classifica\u00e7\u00e3o.IMC<\/th>
Doen\u00e7a.cr\u00f4nica<\/th>
Tempo.de.diagn\u00f3stico<\/th>
Diagn\u00f3stico.Funcional<\/th>
PIM\u00e1x<\/th>
PEM\u00e1x<\/th>
MIF<\/th>
Classifica\u00e7\u00e3o.MIF<\/th>
EAT.10<\/th>
Disfagia<\/th>
DASI<\/th><\/tr><\/thead>
1<\/td>
1<\/td>
70<\/td>
Feminino<\/td>
140<\/td>
60<\/td>
21.42<\/td>
Baixo Peso<\/td>
Hipertens\u00e3o Arterial Sist\u00eamica e Diabetes Mellitus<\/td>
6<\/td>
Hemiparesia \u00e0 esquerda<\/td>
50<\/td>
80<\/td>
125<\/td>
Independ\u00eancia completa<\/td>
0<\/td>
0<\/td>
4.64<\/td><\/tr>
2<\/td>
2<\/td>
63<\/td>
Masculino<\/td>
163<\/td>
80<\/td>
24.53<\/td>
Adequado ou Eutr\u00f3fico<\/td>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
7<\/td>
Hemiparesia \u00e0 direita<\/td>
60<\/td>
160<\/td>
125<\/td>
Independ\u00eancia completa<\/td>
4<\/td>
1<\/td>
5.07<\/td><\/tr>
3<\/td>
3<\/td>
63<\/td>
Masculino<\/td>
165<\/td>
72<\/td>
21.81<\/td>
Baixo Peso<\/td>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
12<\/td>
Hemiparesia \u00e0 esquerda<\/td>
50<\/td>
100<\/td>
119<\/td>
Independ\u00eancia completa<\/td>
0<\/td>
0<\/td>
5.07<\/td><\/tr>
4<\/td>
4<\/td>
64<\/td>
Feminino<\/td>
149<\/td>
61<\/td>
20.46<\/td>
Baixo Peso<\/td>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
48<\/td>
Hemiparesia \u00e0 direita<\/td>
50<\/td>
70<\/td>
126<\/td>
Independ\u00eancia completa<\/td>
0<\/td>
0<\/td>
5.07<\/td><\/tr>
5<\/td>
5<\/td>
70<\/td>
Feminino<\/td>
155<\/td>
58<\/td>
18.7<\/td>
Baixo Peso<\/td>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
6<\/td>
Hemiparesia \u00e0 direita<\/td>
50<\/td>
50<\/td>
115<\/td>
Independ\u00eancia completa<\/td>
0<\/td>
0<\/td>
4.64<\/td><\/tr>
6<\/td>
6<\/td>
68<\/td>
Masculino<\/td>
163<\/td>
78<\/td>
23.92<\/td>
Adequado ou Eutr\u00f3fico<\/td>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
6<\/td>
Hemiparesia \u00e0 esquerda<\/td>
80<\/td>
110<\/td>
123<\/td>
Independ\u00eancia completa<\/td>
0<\/td>
0<\/td>
3.3<\/td><\/tr>
7<\/td>
7<\/td>
67<\/td>
Feminino<\/td>
160<\/td>
78.3<\/td>
24.4<\/td>
Adequado ou Eutr\u00f3fico<\/td>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
132<\/td>
Hemiparesia \u00e0 esquerda<\/td>
60<\/td>
70<\/td>
124<\/td>
Independ\u00eancia completa<\/td>
0<\/td>
0<\/td>
5.5<\/td><\/tr>
8<\/td>
8<\/td>
73<\/td>
Masculino<\/td>
155<\/td>
68.5<\/td>
22.8<\/td>
Adequado ou Eutr\u00f3fico<\/td>
N\u00e3o<\/td>
8<\/td>
Hemiparesia \u00e0 esquerda<\/td>
40<\/td>
50<\/td>
123<\/td>
Independ\u00eancia completa<\/td>
0<\/td>
0<\/td>
3.3<\/td><\/tr>
9<\/td>
9<\/td>
71<\/td>
Masculino<\/td>
165<\/td>
107<\/td>
32.42<\/td>
Sobrepeso<\/td>
N\u00e3o<\/td>
6<\/td>
Hemiparesia \u00e0 esquerda<\/td>
60<\/td>
100<\/td>
126<\/td>
Independ\u00eancia completa<\/td>
0<\/td>
0<\/td>
4.64<\/td><\/tr>
10<\/td>
10<\/td>
60<\/td>
Feminino<\/td>
160<\/td>
60<\/td>
18.75<\/td>
Baixo Peso<\/td>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
12<\/td>
Hemiparesia \u00e0 esquerda<\/td>
80<\/td>
70<\/td>
126<\/td>
Independ\u00eancia completa<\/td>
0<\/td>
0<\/td>
4.64<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
Showing 1 to 10 of 61 entries<\/p>\n\n\n\n
Fun\u00e7\u00f5es do gtsummary<\/h2>\n\n\n\n
O pacote apresenta as seguintes fun\u00e7\u00f5es principais:<\/p>\n\n\n\n
tbl_summary( )<\/em>: calcula estat\u00edsticas descritivas e apresenta os resultados em tabelas resumo;<\/li>
tbl_cross( )<\/em>: compara duas vari\u00e1veis categ\u00f3ricas;<\/li>
tbl_uvregression( )<\/em>: realiza uma regress\u00e3o univariada e retorna uma tabela formatada com as principais estat\u00edsticas do modelo;<\/li>
tbl_regression( )<\/em>: atrav\u00e9s de um objeto de um modelo de regress\u00e3o multivariada retorna uma tabela formatada com as principais estat\u00edsticas do modelo;<\/li>
inline_text( )<\/em>: possibilita a cria\u00e7\u00e3o de relat\u00f3rios reproduz\u00edveis, relatando os resultados das tabelas no texto de um relat\u00f3rio de Markdown.<\/li><\/ul>\n\n\n\n
tbl_summary()<\/em><\/h3>\n\n\n\n
Uso b\u00e1sico<\/h4>\n\n\n\n
Por padr\u00e3o:<\/p>\n\n\n\n
Os tipos de vari\u00e1veis s\u00e3o identificadas e as estat\u00edsticas apropriadas s\u00e3o calculadas.<\/li>
Os atributos de cada vari\u00e1vel do conjunto de dados s\u00e3o impressos automaticamente.<\/li>
Os n\u00edveis de vari\u00e1veis s\u00e3o recuados e notas de rodap\u00e9 s\u00e3o adicionadas.<\/li><\/ul>\n\n\n\n
AVC %>% tbl_summary()<\/code><\/pre>\n\n\n\n
Characteristic<\/strong><\/th>
N = 61<\/strong>1<\/sup><\/th><\/tr><\/thead>
ID<\/td>
31 (16, 46)<\/td><\/tr>
Idade<\/td>
68 (63, 73)<\/td><\/tr>
Sexo<\/td>
<\/td><\/tr>
  Feminino<\/td>
25 (41%)<\/td><\/tr>
  Masculino<\/td>
36 (59%)<\/td><\/tr>
Altura<\/td>
160 (155, 165)<\/td><\/tr>
Peso<\/td>
69 (64, 78)<\/td><\/tr>
IMC<\/td>
24.7 (21.8, 26.9)<\/td><\/tr>
Classifica\u00e7\u00e3o.IMC<\/td>
<\/td><\/tr>
  Adequado ou Eutr\u00f3fico<\/td>
30 (49%)<\/td><\/tr>
  Baixo Peso<\/td>
16 (26%)<\/td><\/tr>
  Sobrepeso<\/td>
15 (25%)<\/td><\/tr>
Doen\u00e7a.cr\u00f4nica<\/td>
<\/td><\/tr>
  Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
37 (61%)<\/td><\/tr>
  Hipertens\u00e3o Arterial Sist\u00eamica e Diabetes Mellitus<\/td>
15 (25%)<\/td><\/tr>
  Hipertens\u00e3o Arterial Sist\u00eamica e Insufici\u00eancia Renal<\/td>
1 (1.6%)<\/td><\/tr>
  N\u00e3o<\/td>
8 (13%)<\/td><\/tr>
Tempo.de.diagn\u00f3stico<\/td>
15 (9, 36)<\/td><\/tr>
Diagn\u00f3stico.Funcional<\/td>
<\/td><\/tr>
  Hemiparesia \u00e0 direita<\/td>
25 (41%)<\/td><\/tr>
  Hemiparesia \u00e0 esquerda<\/td>
36 (59%)<\/td><\/tr>
PIM\u00e1x<\/td>
60 (45, 70)<\/td><\/tr>
PEM\u00e1x<\/td>
70 (50, 80)<\/td><\/tr>
MIF<\/td>
118 (95, 125)<\/td><\/tr>
Classifica\u00e7\u00e3o.MIF<\/td>
<\/td><\/tr>
  Depend\u00eancia modificada at\u00e9 25%<\/td>
13 (21%)<\/td><\/tr>
  Depend\u00eancia modificada at\u00e9 50%<\/td>
6 (9.8%)<\/td><\/tr>
  Independ\u00eancia completa<\/td>
42 (69%)<\/td><\/tr>
EAT.10<\/td>
0 (0, 3)<\/td><\/tr>
Disfagia<\/td>
16 (26%)<\/td><\/tr>
DASI<\/td>
4.47 (3.30, 4.98)<\/td><\/tr>
  Unknown<\/td>
31<\/td><\/tr><\/tbody>
1<\/em> <\/sup>Statistics presented: Median (IQR); n (%)<\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n
\u00c9 poss\u00edvel personalizar a sa\u00edda para ter tabelas mais interessantes<\/p>\n\n\n\n
Fun\u00e7\u00f5es do gtsummary para modificar a apar\u00eancia da tabela<\/li><\/ul>\n\n\n\n
Argumento<\/th>
Descri\u00e7\u00e3o<\/th><\/tr><\/thead>
label<\/td>
especificar as etiquetas das vari\u00e1veis impressas na tabela<\/td><\/tr>
type<\/td>
especifique o tipo de vari\u00e1vel (por exemplo, cont\u00ednua, categ\u00f3rica, etc.)<\/td><\/tr>
by<\/td>
uma vari\u00e1vel na qual as estatisticas resumo ser\u00e3o calculadas separadamente para cada n\u00edvel<\/td><\/tr>
statistic<\/td>
alterar as estat\u00edsticas de resumo apresentadas<\/td><\/tr>
digits<\/td>
n\u00famero de d\u00edgitos que as estat\u00edsticas de resumo ser\u00e3o arredondadas<\/td><\/tr>
missing<\/td>
se deve exibir uma linha com o n\u00famero de observa\u00e7\u00f5es ausentes<\/td><\/tr>
percent<\/td>
imprimir porcentagem de coluna, linha ou c\u00e9lula<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
Fun\u00e7\u00f5es do gtsummary para adicionar informa\u00e7\u00e3o \u00e0 tabela<\/li><\/ul>\n\n\n\n
Fun\u00e7\u00e3o<\/th>
Descri\u00e7\u00e3o<\/th><\/tr><\/thead>
add_p()<\/td>
adicione valores p \u00e0 sa\u00edda comparando valores entre grupos<\/td><\/tr>
add_overall()<\/td>
adicione uma coluna com estat\u00edsticas gerais de resumo<\/td><\/tr>
add_n()<\/td>
adicione uma coluna com N (ou N faltando) para cada vari\u00e1vel<\/td><\/tr>
add_stat_label()<\/td>
adicionar etiqueta para as estat\u00edsticas de resumo mostradas em cada linha<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
Fun\u00e7\u00f5es para formatar a tabela<\/li><\/ul>\n\n\n\n
Fun\u00e7\u00e3o<\/th>
Descri\u00e7\u00e3o<\/th><\/tr><\/thead>
modify_header()<\/td>
atualizar cabe\u00e7alhos de coluna<\/td><\/tr>
modify_footnote()<\/td>
atualizar cabe\u00e7alhos abrangentes<\/td><\/tr>
bold_labels()<\/td>
r\u00f3tulos de vari\u00e1veis em negrito<\/td><\/tr>
bold_levels()<\/td>
n\u00edveis vari\u00e1veis em negrito<\/td><\/tr>
italicize_labels()<\/td>
it\u00e1lico r\u00f3tulos de vari\u00e1veis<\/td><\/tr>
italicize_levels()<\/td>
it\u00e1lico n\u00edveis vari\u00e1veis<\/td><\/tr>
bold_p()<\/td>
valores p significativos em negrito<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
Uso personalizado<\/h4>\n\n\n\n
An\u00e1lise descritiva para vari\u00e1veis num\u00e9ricas<\/li><\/ul>\n\n\n\n
t1 <-\n  AVC %>%\n  select(Idade, Altura, IMC, Peso,PIM\u00e1x, PEM\u00e1x, MIF, DASI ) %>%   \n  tbl_summary(statistic = all_continuous() ~ \"{mean}\", missing = \"no\",\n              digits = list(all_continuous()~ 2)) %>%\n  modify_header(stat_0 ~ \"**M\u00e9dia**\") %>% add_n() \n\nt2 <-\n  AVC %>%\n  select(Idade, Altura, IMC, Peso,PIM\u00e1x, PEM\u00e1x, MIF, DASI ) %>%\n  tbl_summary(statistic = all_continuous() ~ \"{sd}\", missing = \"no\",\n              digits = list(all_continuous()~ 2)) %>%\n  modify_header(stat_0 ~ \"**S.D.**\") \nt3 <-\n  AVC %>%\n  select(Idade, Altura, IMC, Peso,PIM\u00e1x, PEM\u00e1x, MIF, DASI ) %>%\n  tbl_summary(statistic = all_continuous() ~ \"{min}\", missing = \"no\",\n              digits = list(all_continuous()~ 2)) %>%\n  modify_header(stat_0 ~ \"**M\u00edn**\") \nt4 <-\n  AVC %>%\n  select(Idade, Altura, IMC, Peso,PIM\u00e1x, PEM\u00e1x, MIF, DASI ) %>%\n  tbl_summary(statistic = all_continuous() ~ \"{p25}\", missing = \"no\",\n              digits = list(all_continuous()~ 2)) %>%\n  modify_header(stat_0 ~ \"**1\u00baQ**\") \n\nt5 <-\n  AVC %>%\n  select(Idade, Altura, IMC, Peso,PIM\u00e1x, PEM\u00e1x, MIF, DASI ) %>%\n  tbl_summary(statistic = all_continuous() ~ \"{p50}\", missing = \"no\",\n              digits = list(all_continuous()~ 2)) %>%\n  modify_header(stat_0 ~ \"**2\u00baQ**\") \n\nt6 <-\n  AVC %>%\n  select(Idade, Altura, IMC, Peso,PIM\u00e1x, PEM\u00e1x, MIF, DASI ) %>%\n  tbl_summary(statistic = all_continuous() ~ \"{p75}\", missing = \"no\",\n              digits = list(all_continuous()~ 2)) %>%\n  modify_header(stat_0 ~ \"**3\u00baQ**\")\n\nt7 <-\n  AVC %>%\n  select(Idade, Altura, IMC, Peso,PIM\u00e1x, PEM\u00e1x, MIF, DASI ) %>%\n  tbl_summary(statistic = all_continuous() ~ \"{max}\", missing = \"no\",\n              digits = list(all_continuous()~ 2)) %>%\n  modify_header(stat_0 ~ \"**M\u00e1x.**\") \n\ntbl_numerica <- tbl_merge(list(t1, t2,t3,t4,t5,t6,t7)) %>% \n  modify_header(update = list(label  ~  \"**Vari\u00e1veis**\")) %>%  #modificando o nome da coluna\n  modify_footnote(everything() ~ NA_character_) %>% #retiradando os significados das estatisticas\n  modify_spanning_header(everything() ~ NA_character_) #retirando o nome da tabela\ntbl_numerica<\/code><\/pre>\n\n\n\n
Vari\u00e1veis<\/strong><\/th>
N<\/strong><\/th>
M\u00e9dia<\/strong><\/th>
S.D.<\/strong><\/th>
M\u00edn<\/strong><\/th>
1\u00baQ<\/strong><\/th>
2\u00baQ<\/strong><\/th>
3\u00baQ<\/strong><\/th>
M\u00e1x.<\/strong><\/th><\/tr><\/thead>
Idade<\/td>
61<\/td>
69.05<\/td>
7.32<\/td>
60.00<\/td>
63.00<\/td>
68.00<\/td>
73.00<\/td>
87.00<\/td><\/tr>
Altura<\/td>
61<\/td>
160.57<\/td>
9.17<\/td>
140.00<\/td>
155.00<\/td>
160.00<\/td>
165.00<\/td>
184.00<\/td><\/tr>
IMC<\/td>
61<\/td>
24.75<\/td>
4.71<\/td>
15.00<\/td>
21.81<\/td>
24.71<\/td>
26.90<\/td>
41.90<\/td><\/tr>
Peso<\/td>
61<\/td>
70.61<\/td>
10.71<\/td>
43.50<\/td>
64.00<\/td>
69.40<\/td>
77.60<\/td>
107.00<\/td><\/tr>
PIM\u00e1x<\/td>
61<\/td>
58.77<\/td>
17.29<\/td>
25.00<\/td>
45.00<\/td>
60.00<\/td>
70.00<\/td>
100.00<\/td><\/tr>
PEM\u00e1x<\/td>
61<\/td>
70.00<\/td>
23.66<\/td>
20.00<\/td>
50.00<\/td>
70.00<\/td>
80.00<\/td>
160.00<\/td><\/tr>
MIF<\/td>
61<\/td>
108.13<\/td>
21.37<\/td>
50.00<\/td>
95.00<\/td>
118.00<\/td>
125.00<\/td>
126.00<\/td><\/tr>
DASI<\/td>
30<\/td>
4.30<\/td>
1.06<\/td>
2.74<\/td>
3.30<\/td>
4.47<\/td>
4.98<\/td>
6.70<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
An\u00e1lise descritiva para vari\u00e1veis categ\u00f3ricas<\/li><\/ul>\n\n\n\n
categ <- AVC %>%\n  select(Sexo, Disfagia,Classifica\u00e7\u00e3o.IMC, Doen\u00e7a.cr\u00f4nica,Diagn\u00f3stico.Funcional, Classifica\u00e7\u00e3o.MIF, ) %>%\n  tbl_summary(\n    type = all_categorical() ~ \"categorical\") %>% \n  modify_header(update =list(label  ~  \"**Vari\u00e1veis**\"))%>% \n  bold_labels() #n\u00edveis vari\u00e1veis em negrito\ncateg<\/code><\/pre>\n\n\n\n
Vari\u00e1veis<\/strong><\/th>
N = 61<\/strong>1<\/sup><\/th><\/tr><\/thead>
Sexo<\/strong><\/td>
<\/td><\/tr>
Feminino<\/td>
25 (41%)<\/td><\/tr>
Masculino<\/td>
36 (59%)<\/td><\/tr>
Disfagia<\/strong><\/td>
<\/td><\/tr>
0<\/td>
45 (74%)<\/td><\/tr>
1<\/td>
16 (26%)<\/td><\/tr>
Classifica\u00e7\u00e3o.IMC<\/strong><\/td>
<\/td><\/tr>
Adequado ou Eutr\u00f3fico<\/td>
30 (49%)<\/td><\/tr>
Baixo Peso<\/td>
16 (26%)<\/td><\/tr>
Sobrepeso<\/td>
15 (25%)<\/td><\/tr>
Doen\u00e7a.cr\u00f4nica<\/strong><\/td>
<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
37 (61%)<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica e Diabetes Mellitus<\/td>
15 (25%)<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica e Insufici\u00eancia Renal<\/td>
1 (1.6%)<\/td><\/tr>
N\u00e3o<\/td>
8 (13%)<\/td><\/tr>
Diagn\u00f3stico.Funcional<\/strong><\/td>
<\/td><\/tr>
Hemiparesia \u00e0 direita<\/td>
25 (41%)<\/td><\/tr>
Hemiparesia \u00e0 esquerda<\/td>
36 (59%)<\/td><\/tr>
Classifica\u00e7\u00e3o.MIF<\/strong><\/td>
<\/td><\/tr>
Depend\u00eancia modificada at\u00e9 25%<\/td>
13 (21%)<\/td><\/tr>
Depend\u00eancia modificada at\u00e9 50%<\/td>
6 (9.8%)<\/td><\/tr>
Independ\u00eancia completa<\/td>
42 (69%)<\/td><\/tr><\/tbody>
1<\/em> <\/sup>Statistics presented: n (%)<\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n
Tabela de conting\u00eancia<\/li><\/ul>\n\n\n\n
AVC %>%\n  select(Disfagia, Sexo, Classifica\u00e7\u00e3o.IMC,Doen\u00e7a.cr\u00f4nica, Diagn\u00f3stico.Funcional,\n         Classifica\u00e7\u00e3o.MIF,) %>%\n  mutate(Disfagia = factor(Disfagia, labels = c(\"Sem risco\", \"Com Risco\"))) %>%\n  tbl_summary(\n    by = Disfagia, \n    missing = \"no\",\n  ) %>%\n  add_p(pvalue_fun = ~style_pvalue(.x, digits = 3)) %>% \n  modify_header(update =list(label  ~  \"**Vari\u00e1veis**\", p.value ~ \"**Valor-p**\"))%>% \n  bold_labels() %>% \n  bold_p(t = 0.05)<\/code><\/pre>\n\n\n\n
Vari\u00e1veis<\/strong><\/th>
Sem risco<\/strong>, N = 451<\/sup><\/th>
Com Risco<\/strong>, N = 161<\/sup><\/th>
Valor-p<\/strong>2<\/sup><\/th><\/tr><\/thead>
Sexo<\/strong><\/td>
<\/td>
<\/td>
0.973<\/td><\/tr>
Feminino<\/td>
19 (42%)<\/td>
6 (38%)<\/td>
<\/td><\/tr>
Masculino<\/td>
26 (58%)<\/td>
10 (62%)<\/td>
<\/td><\/tr>
Classifica\u00e7\u00e3o.IMC<\/strong><\/td>
<\/td>
<\/td>
0.098<\/td><\/tr>
Adequado ou Eutr\u00f3fico<\/td>
19 (42%)<\/td>
11 (69%)<\/td>
<\/td><\/tr>
Baixo Peso<\/td>
12 (27%)<\/td>
4 (25%)<\/td>
<\/td><\/tr>
Sobrepeso<\/td>
14 (31%)<\/td>
1 (6.2%)<\/td>
<\/td><\/tr>
Doen\u00e7a.cr\u00f4nica<\/strong><\/td>
<\/td>
<\/td>
0.782<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
26 (58%)<\/td>
11 (69%)<\/td>
<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica e Diabetes Mellitus<\/td>
11 (24%)<\/td>
4 (25%)<\/td>
<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica e Insufici\u00eancia Renal<\/td>
1 (2.2%)<\/td>
0 (0%)<\/td>
<\/td><\/tr>
N\u00e3o<\/td>
7 (16%)<\/td>
1 (6.2%)<\/td>
<\/td><\/tr>
Diagn\u00f3stico.Funcional<\/strong><\/td>
<\/td>
<\/td>
0.531<\/td><\/tr>
Hemiparesia \u00e0 direita<\/td>
20 (44%)<\/td>
5 (31%)<\/td>
<\/td><\/tr>
Hemiparesia \u00e0 esquerda<\/td>
25 (56%)<\/td>
11 (69%)<\/td>
<\/td><\/tr>
Classifica\u00e7\u00e3o.MIF<\/strong><\/td>
<\/td>
<\/td>
0.050<\/td><\/tr>
Depend\u00eancia modificada at\u00e9 25%<\/td>
9 (20%)<\/td>
4 (25%)<\/td>
<\/td><\/tr>
Depend\u00eancia modificada at\u00e9 50%<\/td>
2 (4.4%)<\/td>
4 (25%)<\/td>
<\/td><\/tr>
Independ\u00eancia completa<\/td>
34 (76%)<\/td>
8 (50%)<\/td>
<\/td><\/tr><\/tbody>
1<\/em> <\/sup>Statistics presented: n (%)
2<\/em> <\/sup>Statistical tests performed: chi-square test of independence; Fisher’s exact test<\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n
tbl_cross<\/em><\/h3>\n\n\n\n
Adiciona automaticamente um cabe\u00e7alho com o nome ou r\u00f3tulo da vari\u00e1vel de compara\u00e7\u00e3o.<\/li>
Usa percent = \u201ccell\u201d por padr\u00e3o.<\/li>
Adiciona totais de margem de linha e coluna (personaliz\u00e1vel).<\/li><\/ul>\n\n\n\n
tc1 <- AVC %>%\n  tbl_cross(\n    row = Sexo,\n    col = Disfagia,\n    percent = \"column\"\n  ) %>%\n  add_p() \ntc1<\/code><\/pre>\n\n\n\n
<\/th>
DISFAGIA<\/strong><\/th>
DISFAGIA<\/strong><\/th>
<\/th>
<\/th><\/tr>
Characteristic<\/strong><\/th>
0<\/th>
1<\/th>
Total<\/strong><\/th>
p-value<\/strong>1<\/sup><\/th><\/tr><\/thead>
Sexo<\/strong><\/td>
<\/td>
<\/td>
<\/td>
>0.9<\/td><\/tr>
Feminino<\/td>
19 (42%)<\/td>
6 (38%)<\/td>
25 (41%)<\/td>
<\/td><\/tr>
Masculino<\/td>
26 (58%)<\/td>
10 (62%)<\/td>
36 (59%)<\/td>
<\/td><\/tr>
Total<\/strong><\/td>
45 (100%)<\/td>
16 (100%)<\/td>
61 (100%)<\/td>
<\/td><\/tr><\/tbody>
1<\/em> <\/sup>chi-square test of independence<\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n
As fun\u00e7\u00f5es tbl_uvregression()<\/strong> e tbl_regression()<\/strong> do gtsummary fornecem tabelas com as estat\u00edsticas resumo de um modelo de regress\u00e3o. Elas apresentam as mesmas fun\u00e7\u00f5es para personaliza\u00e7\u00e3o<\/p>\n\n\n\n
Argumentos para modificar a apar\u00eancia.<\/li><\/ul>\n\n\n\n
Argumento<\/th>
Descri\u00e7\u00e3o<\/th><\/tr><\/thead>
label<\/td>
modificar r\u00f3tulos de vari\u00e1veis na tabela<\/td><\/tr>
exponentiate<\/td>
exponenciar os coeficientes do modelo<\/td><\/tr>
include<\/td>
nomes das vari\u00e1veis a serem inclu\u00eddas na sa\u00edda. O padr\u00e3o \u00e9 todas as vari\u00e1veis<\/td><\/tr>
show_single_row<\/td>
Por padr\u00e3o, as vari\u00e1veis categ\u00f3ricas s\u00e3o impressas em v\u00e1rias linhas. Se uma vari\u00e1vel \u00e9 dicot\u00f4mica e voc\u00ea deseja imprimir o coeficiente de regress\u00e3o em uma \u00fanica linha, inclua o nome da vari\u00e1vel aqui.<\/td><\/tr>
conf.level<\/td>
n\u00edvel de confian\u00e7a do intervalo de confian\u00e7a<\/td><\/tr>
intercept<\/td>
indica se incluir a intercepta\u00e7\u00e3o<\/td><\/tr>
estimate_fun<\/td>
fun\u00e7\u00e3o para arredondar e formatar estimativas de coeficiente<\/td><\/tr>
pvalue_fun<\/td>
fun\u00e7\u00e3o para arredondar e formatar valores-p<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
tbl_uvregression()<\/em><\/h3>\n\n\n\n
A tbl_uvregression() produz uma tabela de modelos de regress\u00e3o univariada.<\/p>\n\n\n\n
Argumento<\/th>
Descri\u00e7\u00e3o<\/th><\/tr><\/thead>
method<\/td>
m\u00e9todo de regress\u00e3o<\/td><\/tr>
y<\/td>
vari\u00e1vel resposta<\/td><\/tr>
x<\/td>
vari\u00e1veis explicativas. Por padr\u00e3o, todas as outras s\u00e3o selecionadas<\/td><\/tr>
method.args<\/td>
lista de argumentos da regress\u00e3o<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
Uso b\u00e1sico<\/h4>\n\n\n\n
AVC %>%\n  select(Disfagia,Idade, Altura,Peso, IMC, Tempo.de.diagn\u00f3stico, PIM\u00e1x, PEM\u00e1x, MIF, DASI) %>%\n  tbl_uvregression(\n    method = glm,\n    y = Disfagia,\n    method.args = list(family = binomial),\n    exponentiate = TRUE,\n  )<\/code><\/pre>\n\n\n\n
Characteristic<\/strong><\/th>
N<\/strong><\/th>
OR<\/strong>1<\/sup><\/th>
95% CI<\/strong>1<\/sup><\/th>
p-value<\/strong><\/th><\/tr><\/thead>
Idade<\/td>
61<\/td>
1.08<\/td>
0.99, 1.17<\/td>
0.072<\/td><\/tr>
Altura<\/td>
61<\/td>
1.06<\/td>
1.00, 1.14<\/td>
0.078<\/td><\/tr>
Peso<\/td>
61<\/td>
0.99<\/td>
0.93, 1.04<\/td>
0.7<\/td><\/tr>
IMC<\/td>
61<\/td>
0.97<\/td>
0.85, 1.10<\/td>
0.6<\/td><\/tr>
Tempo.de.diagn\u00f3stico<\/td>
61<\/td>
0.99<\/td>
0.96, 1.01<\/td>
0.3<\/td><\/tr>
PIM\u00e1x<\/td>
61<\/td>
0.94<\/td>
0.89, 0.98<\/td>
0.006<\/td><\/tr>
PEM\u00e1x<\/td>
61<\/td>
0.98<\/td>
0.95, 1.01<\/td>
0.2<\/td><\/tr>
MIF<\/td>
61<\/td>
0.97<\/td>
0.94, 1.00<\/td>
0.031<\/td><\/tr>
DASI<\/td>
30<\/td>
0.62<\/td>
0.20, 1.60<\/td>
0.4<\/td><\/tr><\/tbody>
1<\/em> <\/sup>OR = Odds Ratio, CI = Confidence Interval<\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n
Uso personalizado<\/h4>\n\n\n\n
AVC %>%\n  select(Disfagia,Idade, Altura,Peso, IMC, Tempo.de.diagn\u00f3stico, PIM\u00e1x, PEM\u00e1x, MIF, DASI) %>%\n  tbl_uvregression(\n    method = glm,\n    y = Disfagia,\n    method.args = list(family = binomial),\n    exponentiate = TRUE,\n    pvalue_fun = ~style_pvalue(.x, digits = 2))%>%\n  bold_p() %>%         \n  modify_header( \n    update =list(label  ~  \"**Vari\u00e1veis**\" ,\n                 p.value  ~  \"**Valor-p**\",\n                 ci ~ \"**I.C. 95%**\"))<\/code><\/pre>\n\n\n\n
Vari\u00e1veis<\/strong><\/th>
N<\/strong><\/th>
OR<\/strong>1<\/sup><\/th>
I.C. 95%<\/strong>1<\/sup><\/th>
Valor-p<\/strong><\/th><\/tr><\/thead>
Idade<\/td>
61<\/td>
1.08<\/td>
0.99, 1.17<\/td>
0.072<\/td><\/tr>
Altura<\/td>
61<\/td>
1.06<\/td>
1.00, 1.14<\/td>
0.078<\/td><\/tr>
Peso<\/td>
61<\/td>
0.99<\/td>
0.93, 1.04<\/td>
0.70<\/td><\/tr>
IMC<\/td>
61<\/td>
0.97<\/td>
0.85, 1.10<\/td>
0.64<\/td><\/tr>
Tempo.de.diagn\u00f3stico<\/td>
61<\/td>
0.99<\/td>
0.96, 1.01<\/td>
0.27<\/td><\/tr>
PIM\u00e1x<\/td>
61<\/td>
0.94<\/td>
0.89, 0.98<\/td>
0.006<\/td><\/tr>
PEM\u00e1x<\/td>
61<\/td>
0.98<\/td>
0.95, 1.01<\/td>
0.22<\/td><\/tr>
MIF<\/td>
61<\/td>
0.97<\/td>
0.94, 1.00<\/td>
0.031<\/td><\/tr>
DASI<\/td>
30<\/td>
0.62<\/td>
0.20, 1.60<\/td>
0.35<\/td><\/tr><\/tbody>
1<\/em> <\/sup>OR = Odds Ratio, CI = Confidence Interval<\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n
tbl_regression()<\/em><\/h3>\n\n\n\n
A tbl_regression() produz uma tabela de modelos de regress\u00e3o multivariada.<\/p>\n\n\n\n
Uso b\u00e1sico<\/h4>\n\n\n\n
modelo_mult <- lm(MIF ~ Idade + Peso + Altura + Sexo + \n                      Classifica\u00e7\u00e3o.IMC + Doen\u00e7a.cr\u00f4nica+ Disfagia+\n                    Tempo.de.diagn\u00f3stico + Diagn\u00f3stico.Funcional +\n                    PIM\u00e1x + PEM\u00e1x , \n                    AVC)\nr_multi <- modelo_mult %>% \n  tbl_regression()\nr_multi<\/code><\/pre>\n\n\n\n
Characteristic<\/strong><\/th>
Beta<\/strong><\/th>
95% CI<\/strong>1<\/sup><\/th>
p-value<\/strong><\/th><\/tr><\/thead>
Idade<\/td>
-1.3<\/td>
-2.1, -0.45<\/td>
0.003<\/td><\/tr>
Peso<\/td>
0.39<\/td>
-0.36, 1.1<\/td>
0.3<\/td><\/tr>
Altura<\/td>
-0.10<\/td>
-0.78, 0.58<\/td>
0.8<\/td><\/tr>
Sexo<\/td>
<\/td>
<\/td>
<\/td><\/tr>
  Feminino<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td><\/tr>
  Masculino<\/td>
9.9<\/td>
-2.4, 22<\/td>
0.11<\/td><\/tr>
Classifica\u00e7\u00e3o.IMC<\/td>
<\/td>
<\/td>
<\/td><\/tr>
  Adequado ou Eutr\u00f3fico<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td><\/tr>
  Baixo Peso<\/td>
4.1<\/td>
-10, 18<\/td>
0.6<\/td><\/tr>
  Sobrepeso<\/td>
-9.1<\/td>
-24, 5.6<\/td>
0.2<\/td><\/tr>
Doen\u00e7a.cr\u00f4nica<\/td>
<\/td>
<\/td>
<\/td><\/tr>
  Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td><\/tr>
  Hipertens\u00e3o Arterial Sist\u00eamica e Diabetes Mellitus<\/td>
2.1<\/td>
-10, 14<\/td>
0.7<\/td><\/tr>
  Hipertens\u00e3o Arterial Sist\u00eamica e Insufici\u00eancia Renal<\/td>
18<\/td>
-23, 58<\/td>
0.4<\/td><\/tr>
  N\u00e3o<\/td>
3.3<\/td>
-14, 21<\/td>
0.7<\/td><\/tr>
Disfagia<\/td>
-8.9<\/td>
-22, 4.0<\/td>
0.2<\/td><\/tr>
Tempo.de.diagn\u00f3stico<\/td>
0.05<\/td>
-0.09, 0.19<\/td>
0.5<\/td><\/tr>
Diagn\u00f3stico.Funcional<\/td>
<\/td>
<\/td>
<\/td><\/tr>
  Hemiparesia \u00e0 direita<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td><\/tr>
  Hemiparesia \u00e0 esquerda<\/td>
0.24<\/td>
-10.0, 10<\/td>
>0.9<\/td><\/tr>
PIM\u00e1x<\/td>
0.00<\/td>
-0.38, 0.38<\/td>
>0.9<\/td><\/tr>
PEM\u00e1x<\/td>
0.06<\/td>
-0.22, 0.34<\/td>
0.7<\/td><\/tr><\/tbody>
1<\/em> <\/sup>CI = Confidence Interval<\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n
Uso personalizado<\/h4>\n\n\n\n
#regres\u00e3o linear\n\nlinear <- lm(PEM\u00e1x ~ Sexo +Classifica\u00e7\u00e3o.IMC + Doen\u00e7a.cr\u00f4nica\n             + Diagn\u00f3stico.Funcional +Disfagia + Peso+\n               Idade + Altura +  IMC+\n               Tempo.de.diagn\u00f3stico +\n                 PIM\u00e1x + MIF+ DASI, AVC)\ninicial <- linear %>% \n  tbl_regression(pvalue_fun =  ~ style_pvalue ( .x , digits =  3))%>% \n  modify_header(update =list(label  ~  \"**Vari\u00e1veis**\",p.value  ~  \"**Valor-p**\",\n                 ci ~ \"**I.C. 95%**\"))  %>% \n  bold_labels() %>%  #grifa a variavel\n  bold_p(t = 0.05)   #grifa os p valores menores que t\ninicial<\/code><\/pre>\n\n\n\n
Vari\u00e1veis<\/strong><\/th>
Beta<\/strong><\/th>
I.C. 95%<\/strong>1<\/sup><\/th>
Valor-p<\/strong><\/th><\/tr><\/thead>
Sexo<\/strong><\/td>
<\/td>
<\/td>
<\/td><\/tr>
Feminino<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td><\/tr>
Masculino<\/td>
28<\/td>
-8.2, 63<\/td>
0.119<\/td><\/tr>
Classifica\u00e7\u00e3o.IMC<\/strong><\/td>
<\/td>
<\/td>
<\/td><\/tr>
Adequado ou Eutr\u00f3fico<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td><\/tr>
Baixo Peso<\/td>
13<\/td>
-34, 60<\/td>
0.552<\/td><\/tr>
Sobrepeso<\/td>
-8.0<\/td>
-71, 55<\/td>
0.787<\/td><\/tr>
Doen\u00e7a.cr\u00f4nica<\/strong><\/td>
<\/td>
<\/td>
<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica e Diabetes Mellitus<\/td>
0.03<\/td>
-36, 36<\/td>
0.999<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica e Insufici\u00eancia Renal<\/td>
6.4<\/td>
-69, 82<\/td>
0.857<\/td><\/tr>
N\u00e3o<\/td>
-11<\/td>
-70, 47<\/td>
0.689<\/td><\/tr>
Diagn\u00f3stico.Funcional<\/strong><\/td>
<\/td>
<\/td>
<\/td><\/tr>
Hemiparesia \u00e0 direita<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td><\/tr>
Hemiparesia \u00e0 esquerda<\/td>
2.7<\/td>
-28, 34<\/td>
0.855<\/td><\/tr>
Disfagia<\/strong><\/td>
-10<\/td>
-51, 31<\/td>
0.603<\/td><\/tr>
Peso<\/strong><\/td>
-3.7<\/td>
-13, 5.3<\/td>
0.386<\/td><\/tr>
Idade<\/strong><\/td>
-1.9<\/td>
-4.7, 1.0<\/td>
0.177<\/td><\/tr>
Altura<\/strong><\/td>
0.89<\/td>
-3.1, 4.8<\/td>
0.636<\/td><\/tr>
IMC<\/strong><\/td>
16<\/td>
-13, 45<\/td>
0.255<\/td><\/tr>
Tempo.de.diagn\u00f3stico<\/strong><\/td>
-0.04<\/td>
-0.35, 0.28<\/td>
0.803<\/td><\/tr>
PIM\u00e1x<\/strong><\/td>
0.49<\/td>
-0.32, 1.3<\/td>
0.212<\/td><\/tr>
MIF<\/strong><\/td>
0.21<\/td>
-1.3, 1.7<\/td>
0.770<\/td><\/tr>
DASI<\/strong><\/td>
0.89<\/td>
-19, 21<\/td>
0.926<\/td><\/tr><\/tbody>
1<\/em> <\/sup>CI = Confidence Interval<\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n
Usando novamente a fun\u00e7\u00e3o tbl_merge()<\/em> para juntar duas tabelas, podemos cham\u00e1-las de modelo inicial e modelo final<\/p>\n\n\n\n
linear2 <- lm(PEM\u00e1x ~ Sexo +\n               Idade +  \n               PIM\u00e1x, AVC)\nfinal <- linear2 %>% tbl_regression(pvalue_fun =  ~ style_pvalue(.x , digits =  3)) %>% \n          modify_header(update =list(label  ~  \"**Vari\u00e1veis**\" ,\n                 p.value  ~  \"**Valor-p**\")) %>% \n  bold_labels() %>%  #grifa a variavel\n  bold_p(t = 0.05) %>%   #grifa os p valores menores que t\n  modify_header(update =list(label  ~  \"**Vari\u00e1veis**\")) \n\n#Podemos juntar duas tabelas\ntbl_merge_ex2 <-\n  tbl_merge(\n    tbls = list(inicial, final), \n    tab_spanner = c(\"**Modelo inicial**\", \"**Modelo final**\") \n  )\ntbl_merge_ex2<\/code><\/pre>\n\n\n\n
<\/th>
BETA<\/strong><\/th>
I.C. 95%<\/strong>1<\/sup><\/th>
VALOR-P<\/strong><\/th>
BETA<\/strong><\/th>
95% CI<\/strong>1<\/sup><\/th><\/tr><\/thead>
Sexo<\/strong><\/td>
<\/td>
<\/td>
<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Feminino<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td><\/tr>
Masculino<\/td>
28<\/td>
-8.2, 63<\/td>
0.119<\/td>
11<\/td>
0.51, 21<\/td>
0.040<\/td><\/tr>
Classifica\u00e7\u00e3o.IMC<\/strong><\/td>
<\/td>
<\/td>
<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Adequado ou Eutr\u00f3fico<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Baixo Peso<\/td>
13<\/td>
-34, 60<\/td>
0.552<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Sobrepeso<\/td>
-8.0<\/td>
-71, 55<\/td>
0.787<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Doen\u00e7a.cr\u00f4nica<\/strong><\/td>
<\/td>
<\/td>
<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica e Diabetes Mellitus<\/td>
0.03<\/td>
-36, 36<\/td>
0.999<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Hipertens\u00e3o Arterial Sist\u00eamica e Insufici\u00eancia Renal<\/td>
6.4<\/td>
-69, 82<\/td>
0.857<\/td>
<\/td>
<\/td>
<\/td><\/tr>
N\u00e3o<\/td>
-11<\/td>
-70, 47<\/td>
0.689<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Diagn\u00f3stico.Funcional<\/strong><\/td>
<\/td>
<\/td>
<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Hemiparesia \u00e0 direita<\/td>
\u2014<\/td>
\u2014<\/td>
<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Hemiparesia \u00e0 esquerda<\/td>
2.7<\/td>
-28, 34<\/td>
0.855<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Disfagia<\/strong><\/td>
-10<\/td>
-51, 31<\/td>
0.603<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Peso<\/strong><\/td>
-3.7<\/td>
-13, 5.3<\/td>
0.386<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Idade<\/strong><\/td>
-1.9<\/td>
-4.7, 1.0<\/td>
0.177<\/td>
-0.90<\/td>
-1.6, -0.18<\/td>
0.015<\/td><\/tr>
Altura<\/strong><\/td>
0.89<\/td>
-3.1, 4.8<\/td>
0.636<\/td>
<\/td>
<\/td>
<\/td><\/tr>
IMC<\/strong><\/td>
16<\/td>
-13, 45<\/td>
0.255<\/td>
<\/td>
<\/td>
<\/td><\/tr>
Tempo.de.diagn\u00f3stico<\/strong><\/td>
-0.04<\/td>
-0.35, 0.28<\/td>
0.803<\/td>
<\/td>
<\/td>
<\/td><\/tr>
PIM\u00e1x<\/strong><\/td>
0.49<\/td>
-0.32, 1.3<\/td>
0.212<\/td>
0.54<\/td>
0.23, 0.86<\/td>
0.001<\/td><\/tr>
MIF<\/strong><\/td>
0.21<\/td>
-1.3, 1.7<\/td>
0.770<\/td>
<\/td>
<\/td>
<\/td><\/tr>
DASI<\/strong><\/td>
0.89<\/td>
-19, 21<\/td>
0.926<\/td>
<\/td>
<\/td>
<\/td><\/tr><\/tbody>
1<\/em> <\/sup>CI = Confidence Interval<\/td><\/tr><\/tfoot><\/table><\/figure>\n\n\n\n
inline_text()<\/em><\/h3>\n\n\n\n
Resultados de uma regress\u00e3o de forma reproduz\u00edvel<\/h4>\n\n\n\n
`r inline_text(tabela, variable = ,pattern = \"{}\")`<\/code><\/pre>\n\n\n\n
Argumentos:<\/p>\n\n\n\n
nome da tabela<\/li>
variable: a vari\u00e1vel que deseja ter os resultados<\/li>
pattern: as estat\u00edsticas que ser\u00e3o imprimidas entre chaves e aspas ({estimate},{conf.low},{conf.high},{p.value},{conf.level},{N})<\/li><\/ul>\n\n\n\n
<\/figure>\n\n\n\n
Houve influ\u00eancia significativa (valor- p=0.001) e positiva (\u03b2 = 0.54) do PIM\u00e1x sobre a PEM\u00e1x. Sendo assim, a cada uma unidade acrescida no PIM\u00e1x, espera-se um aumento m\u00e9dio de 0.54 unidades na PEM\u00e1x.<\/p>\n\n\n\n
<\/figure>\n\n\n\n
Houve influ\u00eancia significativa (valor- p=0.015)) e negativa (\u03b2 = -0.90) da Idade sobre a PEM\u00e1x. Sendo assim, a cada uma unidade acrescida na Idade, espera-se um diminui\u00e7\u00e3o m\u00e9dia de -0.90 unidades na PEM\u00e1x.<\/p>\n\n\n\n
Resultados de uma an\u00e1lise descritiva de forma reproduz\u00edvel<\/h4>\n\n\n\n
`r inline_text(tabela, variable = , column = ,level = ,pattern = \"{}\")`<\/code><\/pre>\n\n\n\n
Argumentos:<\/p>\n\n\n\n
nome da tabela;<\/li>
variable: a vari\u00e1vel que deseja ter os resultados;<\/li>
column: n\u00edvel da vari\u00e1vel escolhida (coluna);<\/li>
level: n\u00edvel da vari\u00e1vel categ\u00f3rica (linha);<\/li>
pattern: as estat\u00edsticas que devem ser imprimidas entre aspas e chaves( ).<\/li><\/ul>\n\n\n\n
<\/figure>\n\n\n\n
Os indiv\u00edduos apresentaram, em m\u00e9dia, 69.05 anos, com desvio padr\u00e3o de 7.32. A idade m\u00ednima observada foi 60.00 e a idade m\u00e1xima foi 87.00<\/p>\n\n\n\n
<\/figure>\n\n\n\n
A maioria dos indiv\u00edduos (59%) \u00e9 do sexo masculino.<\/p>\n\n\n\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
O pacote gtsummary\u00a0utiliza todos os recursos do pacote gt para criar tabelas anal\u00edticas e de resumo prontas para a publica\u00e7\u00e3o.<\/p>\n","protected":false},"author":8,"featured_media":7070,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"","site-content-layout":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","spay_email":"","footnotes":""},"categories":[445],"tags":[104,294,247,295,296],"class_list":["post-7058","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ferramentas-e-tecnologias","tag-dados","tag-gtsummary","tag-pacote","tag-resumo","tag-tabelas"],"yoast_head":"\n