# Create Tables from Different Types of Regression

Create regression tables from generalized linear model(GLM), generalized estimating equation(GEE), generalized linear mixed-effects model(GLMM), Cox proportional hazards model, survey-weighted generalized linear model(svyglm) and survey-weighted Cox model results for publication.

Regression Tables from 'GLM', 'GEE', 'GLMM', 'Cox' and 'survey' Results for Publication.

## GLM Table

``````## \$first.line
## [1] "Linear regression predicting mpg\n"
##
## \$table
##      crude coeff.(95%CI)   crude P value adj. coeff.(95%CI)
## cyl  "-2.88 (-3.51,-2.24)" "< 0.001"     "-1.59 (-2.98,-0.19)"
## disp "-0.04 (-0.05,-0.03)" "< 0.001"     "-0.02 (-0.04,0)"
## cyl  "0.034"
## disp "0.054"
##
## \$last.lines
## [1] "No. of observations = 32\nR-squared = 0.7596\nAIC value = 167.1456\n\n"
##
## attr(,"class")
## [1] "display" "list"
``````
``````## \$first.line
## [1] "Logistic regression predicting vs\n"
##
## \$table
## cyl  "0.2 (0.08,0.56)"  "0.002"       "0.15 (0.02,1.02)" "0.053"
## disp "0.98 (0.97,0.99)" "0.002"       "1 (0.98,1.03)"    "0.715"
##
## \$last.lines
## [1] "No. of observations = 32\nAIC value = 23.8304\n\n"
##
## attr(,"class")
## [1] "display" "list"
``````

## GEE Table: from `geeglm` object from geepack package

``````## \$caption
## [1] "GEE(gaussian) predicting Weight by Time, Cu - Group Pig"
##
## \$table
##            crude coeff(95%CI)   crude P value adj. coeff(95%CI)
## Time       "6.94 (6.79,7.1)"    "< 0.001"     "6.94 (6.79,7.1)"
## Cu: ref.=1 NA                   NA            NA
##    2       "-0.59 (-3.73,2.54)" "0.711"       "-0.84 (-3.9,2.23)"
##    3       "1.9 (-1.87,5.66)"   "0.324"       "1.77 (-1.9,5.45)"
## Time       "< 0.001"
## Cu: ref.=1 NA
##    2       "0.593"
##    3       "0.345"
##
## \$metric
##                                  crude coeff(95%CI) crude P value
##                                  NA                 NA
## Estimated correlation parameters "0.775"            NA
## No. of clusters                  "72"               NA
## No. of observations              "861"              NA
##                                  NA                NA
## Estimated correlation parameters NA                NA
## No. of clusters                  NA                NA
## No. of observations              NA                NA
``````
``````## \$caption
## [1] "GEE(binomial) predicting ddn by Time, Cu - Group Pig"
##
## \$table
##            crude OR(95%CI)    crude P value adj. OR(95%CI)
## Time       "0.99 (0.96,1.03)" "0.785"       "0.99 (0.96,1.03)"
## Cu: ref.=1 NA                 NA            NA
##    2       "1.14 (0.79,1.65)" "0.485"       "1.14 (0.79,1.65)"
##    3       "1.06 (0.72,1.57)" "0.76"        "1.06 (0.72,1.57)"
## Time       "0.783"
## Cu: ref.=1 NA
##    2       "0.484"
##    3       "0.76"
##
## \$metric
##                                  crude OR(95%CI) crude P value
##                                  NA              NA
## Estimated correlation parameters "0.026"         NA
## No. of clusters                  "72"            NA
## No. of observations              "861"           NA
##                                  NA             NA
## Estimated correlation parameters NA             NA
## No. of clusters                  NA             NA
## No. of observations              NA             NA
``````

## Mixed model Table: `lmerMod` or `glmerMod` object from lme4 package

``````## \$table
##                       crude coeff(95%CI) crude P value adj. coeff(95%CI)
## Time                    6.94 (6.88,7.01)     0.0000000  6.94 (6.88,7.01)
## Cu: ref.=1                          <NA>            NA              <NA>
##    2                  -0.57 (-4.66,3.52)     0.7837028 -0.81 (-4.42,2.8)
##    3                    1.9 (-2.23,6.04)     0.3666829 1.78 (-1.87,5.43)
## Random effects                      <NA>            NA              <NA>
## Pig                  39.71 (27.82,54.93)            NA              <NA>
## Evit                       0.9 (0,13.45)            NA              <NA>
## Residual              11.37 (10.3,12.55)            NA              <NA>
## Metrics                             <NA>            NA              <NA>
## No. of groups (Pig)                   72            NA              <NA>
## No. of groups (Evit)                   3            NA              <NA>
## No. of observations                  861            NA              <NA>
## Log-likelihood                  -2400.69            NA              <NA>
## AIC value                        4801.38            NA              <NA>
## Time                    0.0000000
## Cu: ref.=1                     NA
##    2                    0.6598522
##    3                    0.3393579
## Random effects                 NA
## Pig                            NA
## Evit                           NA
## Residual                       NA
## Metrics                        NA
## No. of groups (Pig)            NA
## No. of groups (Evit)           NA
## No. of observations            NA
## Log-likelihood                 NA
## AIC value                      NA
##
## \$caption
## [1] "Linear mixed model fit by REML : Weight ~ Time + Cu + (1 | Pig) + (1 | Evit)"
``````
``````## \$table
##                      crude OR(95%CI) crude P value   adj. OR(95%CI)
## Weight                 1 (0.99,1.01)     0.9358643 1.01 (0.99,1.03)
## Time                0.99 (0.96,1.03)     0.7905865  0.95 (0.81,1.1)
## Random effects                  <NA>            NA             <NA>
## Pig                              0.1            NA             <NA>
## Metrics                         <NA>            NA             <NA>
## No. of groups (Pig)               72            NA             <NA>
## No. of observations              861            NA             <NA>
## Log-likelihood                -594.2            NA             <NA>
## AIC value                     1196.4            NA             <NA>
## Weight                 0.4925311
## Time                   0.4642975
## Random effects                NA
## Pig                           NA
## Metrics                       NA
## No. of groups (Pig)           NA
## No. of observations           NA
## Log-likelihood                NA
## AIC value                     NA
##
## \$caption
## [1] "Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) : ddn ~ Weight + Time + (1 | Pig)"
``````

## Cox model with `frailty` or `cluster` options

``````## \$table
## ph.ecog "1.61 (1.25,2.08)" "< 0.001"     "1.56 (1.22,2)" "< 0.001"
## age     "1.02 (1.01,1.03)" "0.007"       "1.01 (1,1.02)" "0.085"
##
## \$ranef
##         [,1] [,2] [,3] [,4]
## cluster   NA   NA   NA   NA
## inst      NA   NA   NA   NA
##
## \$metric
##                     [,1] [,2] [,3] [,4]
## <NA>                  NA   NA   NA   NA
## No. of observations  226   NA   NA   NA
## No. of events        163   NA   NA   NA
##
## \$caption
## [1] "Marginal Cox model on time ('time') to event ('status') - Group inst"
``````
``````## \$table
## ph.ecog "1.64 (1.31,2.05)" "< 0.001"     "1.58 (1.26,1.99)" "< 0.001"
## age     "1.02 (1,1.04)"    "0.041"       "1.01 (0.99,1.03)" "0.225"
##
## \$ranef
##         [,1] [,2] [,3] [,4]
## frailty   NA   NA   NA   NA
## inst      NA   NA   NA   NA
##
## \$metric
##                     [,1] [,2] [,3] [,4]
## <NA>                  NA   NA   NA   NA
## No. of observations  226   NA   NA   NA
## No. of events        163   NA   NA   NA
##
## \$caption
## [1] "Frailty Cox model on time ('time') to event ('status') - Group inst"
``````

## Cox mixed effect model Table: `coxme` object from coxme package

``````## \$table
## ph.ecog "1.66 (1.32,2.09)" "< 0.001"     "1.61 (1.27,2.03)" "< 0.001"
## age     "1.02 (1,1.04)"    "0.043"       "1.01 (0.99,1.03)" "0.227"
##
## \$ranef
##                 [,1] [,2] [,3] [,4]
## Random effect     NA   NA   NA   NA
## inst(Intercept) 0.02   NA   NA   NA
##
## \$metric
##                     [,1] [,2] [,3] [,4]
## <NA>                  NA   NA   NA   NA
## No. of groups(inst)   18   NA   NA   NA
## No. of observations  226   NA   NA   NA
## No. of events        163   NA   NA   NA
##
## \$caption
## [1] "Mixed effects Cox model on time ('time') to event ('status') - Group inst"
``````

## GLM for survey data : `svyglm` object from survey package

``````## \$first.line
## [1] "Linear regression predicting api00- weighted data\n"
##
## \$table
##             crude coeff.(95%CI)    crude P value adj. coeff.(95%CI)
## ell         "-3.73 (-4.35,-3.11)"  "< 0.001"     "-0.48 (-1.25,0.29)"
## meals       "-3.38 (-3.71,-3.05)"  "< 0.001"     "-3.14 (-3.69,-2.59)"
## mobility    "-1.43 (-3.3,0.44)"    "0.137"       "0.22 (-0.55,0.99)"
## tt2: 1 vs 0 "10.98 (-34.16,56.12)" "0.634"       "6.13 (-17.89,30.15)"
## ell         "0.222"
## meals       "< 0.001"
## mobility    "0.573"
## tt2: 1 vs 0 "0.618"
##
## \$last.lines
## [1] "No. of observations = 200\nAIC value = 2309.8282\n\n"
##
## attr(,"class")
## [1] "display" "list"
``````
``````## \$first.line
## [1] "Logistic regression predicting tt- weighted data\n"
##
## \$table
##             crude OR.(95%CI)   crude P value adj. OR.(95%CI)
## ell         "1.02 (1,1.05)"    "0.047"       "1.11 (1.03,1.21)"
## meals       "1.01 (0.99,1.03)" "0.255"       "0.95 (0.91,1)"
## mobility    "1.01 (0.98,1.03)" "0.506"       "1.1 (0.98,1.23)"
## tt2: 1 vs 0 "0 (0,0)"          "< 0.001"     "0 (0,0)"
## ell         "0.009"
## meals       "0.068"
## mobility    "0.114"
## tt2: 1 vs 0 "< 0.001"
##
## \$last.lines
## [1] "No. of observations = 200\n\n"
##
## attr(,"class")
## [1] "display" "list"
``````

## Cox model for survey data :`svycoxph` object from survey package

``````## Stratified Independent Sampling design (with replacement)
## svydesign(id = ~1, prob = ~randprob, strata = ~edema, data = subset(pbc,
##     randomized))
## Stratified Independent Sampling design (with replacement)
## svydesign(id = ~1, prob = ~randprob, strata = ~edema, data = subset(pbc,
##     randomized))
## Stratified Independent Sampling design (with replacement)
## svydesign(id = ~1, prob = ~randprob, strata = ~edema, data = subset(pbc,
##     randomized))
## Stratified Independent Sampling design (with replacement)
## svydesign(id = ~1, prob = ~randprob, strata = ~edema, data = subset(pbc,
##     randomized))
## Stratified Independent Sampling design (with replacement)
## svydesign(id = ~1, prob = ~randprob, strata = ~edema, data = subset(pbc,
##     randomized))

## \$table
##               crude HR(95%CI)      crude P value adj. HR(95%CI)
## sex: f vs m   "0.62 (0.4,0.97)"    "0.038"       "0.55 (0.33,0.9)"
## protime       "1.37 (1.09,1.72)"   "0.006"       "1.52 (1.2,1.91)"
## albumin       "0.2 (0.14,0.29)"    "< 0.001"     "0.31 (0.2,0.47)"
## stage: ref.=1 NA                   NA            NA
##    2          "5.67 (0.77,41.78)"  "0.089"       "10.94 (1.01,118.55)"
##    3          "9.78 (1.37,69.94)"  "0.023"       "17.03 (1.69,171.6)"
##    4          "22.89 (3.2,163.48)" "0.002"       "22.56 (2.25,226.42)"
## sex: f vs m   "0.017"
## protime       "< 0.001"
## albumin       "< 0.001"
## stage: ref.=1 NA
##    2          "0.049"
##    3          "0.016"
##    4          "0.008"
##
## \$metric
##                        [,1] [,2] [,3] [,4]
## <NA>                     NA   NA   NA   NA
## No. of observations  312.00   NA   NA   NA
## No. of events        144.00   NA   NA   NA
## AIC                 1483.12   NA   NA   NA
##
## \$caption
## [1] "Survey cox model on time ('time') to event ('status > 0')"
``````

## Sub-group analysis for Cox/svycox model

``````##   Variable Count Percent Point Estimate Lower Upper    0    1 P value
## 1  Overall   228     100           1.91  1.14   3.2 41.3 58.7   0.014
## 2     <NA>  <NA>    <NA>           <NA>  <NA>  <NA> <NA> <NA>    <NA>
## 3       kk  <NA>    <NA>           <NA>  <NA>  <NA> <NA> <NA>    <NA>
## 4        0    38      38           2.88  0.31 26.49   20   80    0.35
## 5        1   187     187           1.84  1.08  3.14 43.1 56.9   0.026
## 6     <NA>  <NA>    <NA>           <NA>  <NA>  <NA> <NA> <NA>    <NA>
## 7      kk1  <NA>    <NA>           <NA>  <NA>  <NA> <NA> <NA>    <NA>
## 8        0     8       8           <NA>  <NA>  <NA>    0  100    <NA>
## 9        1   217     217           1.88  1.12  3.17 42.6 57.4   0.018
##   P for interaction
## 1              <NA>
## 2              <NA>
## 3             0.525
## 4              <NA>
## 5              <NA>
## 6              <NA>
## 7             0.997
## 8              <NA>
## 9              <NA>
``````
``````## Independent Sampling design (with replacement)
## svydesign(id = ~1, data = lung)
## Independent Sampling design (with replacement)
## svydesign(id = ~1, data = lung)
## Independent Sampling design (with replacement)
## subset(data, get(var_subgroup) == .)
## Independent Sampling design (with replacement)
## subset(data, get(var_subgroup) == .)
## Independent Sampling design (with replacement)
## svydesign(id = ~1, data = lung)
## Independent Sampling design (with replacement)
## subset(data, get(var_subgroup) == .)

##   Variable Count Percent Point Estimate Lower Upper    0    1 P value
## 1  Overall   228     100           1.91  1.14  3.19 41.3 58.7   0.013
## 2       kk  <NA>    <NA>           <NA>  <NA>  <NA> <NA> <NA>    <NA>
## 3        0    38      38           2.88  0.31  27.1   20   80   0.355
## 4        1   187     187           1.84  1.08  3.11 43.1 56.9   0.024
## 5      kk1  <NA>    <NA>           <NA>  <NA>  <NA> <NA> <NA>    <NA>
## 6        0  <NA>    <NA>           <NA>  <NA>  <NA> <NA> <NA>    <NA>
## 7        1   217     217           1.88  1.12  3.15 42.6 57.4   0.017
##   P for interaction
## 1              <NA>
## 2             0.523
## 3              <NA>
## 4              <NA>
## 5            <0.001
## 6              <NA>
## 7              <NA>
``````

# jstable 0.8.1

## Update

• `CreateTableOneJS` and `svyCreateTableOneJS` can get simplified table with showAllLevels == F option.

# jstable 0.8.0

## New function

• `TableSubgroupMultiCox`: Get sub-group analysis table for forestplot with Cox/svycox model.

# jstable 0.7.10

• Update `CreateTableOneJS` and `svyCreateTableOneJS` according to tableone package(0.10.0).

# jstable 0.7.9

• Add namespace survival::cluster, survival::frailty to `cox2.display`

# jstable 0.7.8

• Remove 2 packages to Import: DT, epiDisplay.

# jstable 0.7.7

• Fix typo in DESCRIPTION.

# jstable 0.7.6

• Fix description text and some examples for cran release.

# jstable 0.7.5

• Change package Title for cran release.

# jstable 0.7.4

## Bug fixes

• Fix some spell for cran release

## Update

• Update travis-ci

• Add appveyor CI to test window environment

# jstable 0.7.3

## Update

• Add R-squared to `glmshow.display`

# jstable 0.7.2

## Bug fixes

• `svyCreateTableOne2`, `svyCreateTableOneJS`, `LabelJsTable`, `LabelepiDisplay` and `svyregress.display`

## Update

• `coefNA` can be used in `svyregress.display`

# jstable 0.7.1

## Bug fixes

• `svyglm` function.

• Apply testhat.

# jstable 0.7.0

## Update

• Auto-selection between Chi-square test and Fisher's exact test in `CreateTableOneJS`, `CreateTableOne2`.

• Table 1 for survey data: `svyCreateTableOne2` and `svyCreateTableOneJS` are modified functions of `svyCreateTableOne`(tableone package).

# jstable 0.6.9

• New function: `coefNA`

• Bug fixes: Coefficients in `glmshow.display`, `cox2.display`

# jstable 0.6.8

• Bug fixes: data.frame & cluster model issue in `cox2.display`

# jstable 0.6.7

• Bug fixes : duplicate variable name - `glmshow.display`, `cox2.display`, `geeglm.display`, `coxme.display`

# jstable 0.6.5

## New function

• `glmshow.display`: table from `glm.object`.

## Bug fixes

• `LabelepiDisplay`: column name issue.

# jstable 0.6.3

## New function

• `svycox.display`: table from `svycoxph.object` in survey package

# jstable 0.6.2

## New function

• `svyregress.display`: table from `svyglm.object` in survey package

# jstable 0.6.1

• Update: `cox2.display` function allows `data` argument.

• Remove `jsBasicGadget` : Move to jsmodule package.

# jstable 0.6.0

• Shiny gadget for descriptive statistics: `jsBasicGadget`

• Rstudio Addin of `jsBasicGadget`: `jsBasicAddin`

# jstable 0.5.2

• Bug fixes: `geeExp`, `lmerExp` function

# jstable 0.5.1

• Bug fixes: `coxExp`, `cox2.display` function

# jstable 0.5.0

## New function

• Table from `coxph.object` (survival package) - allow `cluster` & `frailty` options: `cox2.display` function

• Apply label information to `cox2.display`: `LabeljsCox` function

• Apply label information to `geeglm.display`: `LabeljsGeeglm` function

## Bug fixes

• Bug fixes: `geeglm.display` function

# jstable 0.4.5

• Apply label information to `epiDisplay.object`: `LabelepiDisplay` function

• Apply label information to `lmer.display`, `coxme.display`: `LabeljsMixed` function

# jstable 0.4.0

## New function

• Table from `coxme.object` (coxme package): `coxme.display` function

## Bug fixes

• Bug fixes: 1 variable case.

# jstable 0.3.5

• Change default page length option of `opt.tb1` from 10 to 25.

# Reference manual

install.packages("jstable")

0.8.2 by Jinseob Kim, 11 days ago

https://github.com/jinseob2kim/jstable

Report a bug at https://github.com/jinseob2kim/jstable/issues

Browse source code at https://github.com/cran/jstable

Authors: Jinseob Kim [aut, cre] , Zarathu [cph, fnd]

Documentation:   PDF Manual