UNITAB



Stata help for unitab

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help for unitab
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Univariate table

        unitab depvar [varlist1] [if exp] [in range] [, level(#) format(%fmt)  categorical(varlist2) exact]

Description

    unitab displays a univariate table with the maximum-likelihood estimates of odds ratio and confidence intervals using logit command and
       some useful information using tabulate command.

    dep_var binary dependent variable that must be coded as
    
                   depvar = 0    or
                   depvar = #    with # > 0


    varlist1 covariates treated as continuous.
    varlist2 covariates treated as categorical.
    
You can specify the same variable as continuous and/or categorical. First results are displayed for continuous variables and then for
       categorical variables.

Explanation of the table

Continuous variable

        1 column : summarize depvar if continuous_variable == #

        2 column : total observations

        3 column : point estimate of odds ratio using maximum likelihood estimators logit

        4-5 columns : lower and upper bound for odds ratio at a certain level(#)

        6 column : statistical significance of the odds ratio using a Wald test
 
Categorical variable

        1 column : tabulate depvar categorical_variable (display only for depvar = # )

        2 column : total observations for each category

        3 column : point estimate of odds ratio using maximum likelihood estimators

        4-5 columns : lower and upper bound for odds ratio at a certain level(#)

        6 column : statistical significance of the Pearson's chi-squared test for the hypothesis that the rows and columns in a two-way
                   table are independent

Options

      level(#)  specifies the confidence level, in percent, for calculation of confidence intervals of the odds ratios; see help level.

      format(%fmt) specifies the display format for odds ratio and confidence intervals in the univariate table. format(%4.3f) is the default;
                format(%6.5f) is a popular alternative.

     categorical(varlist2) specifies the variables that you want treat as categorical.

     exact displays the significance calculated by Fisher's exact. We recommend specifying exact whenever samples are small.

Examples
   
      . webuse lbw, clear
      . tab low
      . su age
      . su age if low == 1
      . logistic low age
      . unitab low age
      . xtile ageq = age, nq(4)
      . tab ageq low, row nokey
      . xi: logistic low i.ageq
      . unitab low, c(ageq)
      . unitab low age, c(ageq)
      . tab race low, row nokey
      . xi:logistic low i.race
      . unitab low , c(race)
      . unitab low age ht ui, c(race smoke ageq)
      . unitab low age ht ui, c(race smoke ageq) l(90) f(%6.5f) 

Authors

    Nicola Orsini, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden and Institute of Information Science and
    Technology, National Research Council of Italy, Pisa, Italy.

    Matteo Bottai, Arnold School of Public Health, University of South Carolina, Columbia, USA and Institute of Information Science and
    Technology, National Research Council of Italy, Pisa, Italy.

Also see

           [R] logistic
           [R] tabulate

On-line:  help for help for logistic, tabulate, summarize

Worked examples for unitab

Click here to run or save the do-file for the following worked examples and be sure to have an update version. Type
. capture net install http://nicolaorsini.altervista.org/stata/unitab

. which unitab
c:\ado\plus\u\unitab.ado
*! version 1.0  22 Sep 2003 N.Orsini & M.Bottai
*! version 2.0  26 Sep 2003 N.Orsini & M.Bottai  
*! version 3.0  04 Apr 2004 N.Orsini & M.Bottai (only changed help file)

. webuse lbw, clear
(Hosmer & Lemeshow data)

. tab low 

      birth |
weight<2500 |
          g |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |        130       68.78       68.78
          1 |         59       31.22      100.00
------------+-----------------------------------
      Total |        189      100.00

. su age  

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
         age |       189     23.2381    5.298678         14         45

. su age if low == 1   

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
         age |        59    22.30508    4.511496         14         34

. logistic low age   

Logistic regression                               Number of obs   =        189
                                                  LR chi2(1)      =       2.76
                                                  Prob > chi2     =     0.0966
Log likelihood = -115.95598                       Pseudo R2       =     0.0118

------------------------------------------------------------------------------
         low | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |   .9501333   .0299423    -1.62   0.105     .8932232    1.010669
------------------------------------------------------------------------------

. unitab low age  
------------------------------------------------------------------------------
     low    |    low=1(%)      Total(%)     OR   [95% Conf. Interval]  p-value
------------+-----------------------------------------------------------------
     age    |      59(31)       189(100)   0.950    0.893     1.011     0.105
------------------------------------------------------------------------------

. xtile ageq = age, nq(4)  

. tab ageq low, row nokey chi2  

         4 |
 quantiles |  birth weight<2500g
    of age |         0          1 |     Total
-----------+----------------------+----------
         1 |        36         15 |        51 
           |     70.59      29.41 |    100.00 
-----------+----------------------+----------
         2 |        36         20 |        56 
           |     64.29      35.71 |    100.00 
-----------+----------------------+----------
         3 |        21         15 |        36 
           |     58.33      41.67 |    100.00 
-----------+----------------------+----------
         4 |        37          9 |        46 
           |     80.43      19.57 |    100.00 
-----------+----------------------+----------
     Total |       130         59 |       189 
           |     68.78      31.22 |    100.00 

          Pearson chi2(3) =   5.3442   Pr = 0.148

. tab ageq low, row nokey exact      

         4 |
 quantiles |  birth weight<2500g
    of age |         0          1 |     Total
-----------+----------------------+----------
         1 |        36         15 |        51 
           |     70.59      29.41 |    100.00 
-----------+----------------------+----------
         2 |        36         20 |        56 
           |     64.29      35.71 |    100.00 
-----------+----------------------+----------
         3 |        21         15 |        36 
           |     58.33      41.67 |    100.00 
-----------+----------------------+----------
         4 |        37          9 |        46 
           |     80.43      19.57 |    100.00 
-----------+----------------------+----------
     Total |       130         59 |       189 
           |     68.78      31.22 |    100.00 

           Fisher's exact =                 0.143

. xi: logistic low i.ageq   
i.ageq            _Iageq_1-4          (naturally coded; _Iageq_1 omitted)

Logistic regression                               Number of obs   =        189
                                                  LR chi2(3)      =       5.50
                                                  Prob > chi2     =     0.1383
Log likelihood = -114.58352                       Pseudo R2       =     0.0235

------------------------------------------------------------------------------
         low | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _Iageq_2 |   1.333333   .5533289     0.69   0.488     .5911435    3.007354
    _Iageq_3 |   1.714286   .7832056     1.18   0.238      .700156    4.197316
    _Iageq_4 |   .5837838   .2815403    -1.12   0.264     .2268531    1.502309
------------------------------------------------------------------------------

. unitab low, c(ageq) 
------------------------------------------------------------------------------
     low    |    low=1(%)      Total(%)     OR   [95% Conf. Interval]  p-value
------------+-----------------------------------------------------------------
    ageq  1 |      15(29)        51(27)     .        .         .        0.148
          2 |      20(36)        56(30)    1.333    0.591     3.007
          3 |      15(42)        36(19)    1.714    0.700     4.197
          4 |       9(20)        46(24)    0.584    0.227     1.502
------------------------------------------------------------------------------

. unitab low, c(ageq) exact 
------------------------------------------------------------------------------
     low    |    low=1(%)      Total(%)     OR   [95% Conf. Interval]  p-value
------------+-----------------------------------------------------------------
    ageq  1 |      15(29)        51(27)     .        .         .        0.143
          2 |      20(36)        56(30)    1.333    0.591     3.007
          3 |      15(42)        36(19)    1.714    0.700     4.197
          4 |       9(20)        46(24)    0.584    0.227     1.502
------------------------------------------------------------------------------

. unitab low age, c(ageq)  
------------------------------------------------------------------------------
     low    |    low=1(%)      Total(%)     OR   [95% Conf. Interval]  p-value
------------+-----------------------------------------------------------------
     age    |      59(31)       189(100)   0.950    0.893     1.011     0.105
------------+-----------------------------------------------------------------
    ageq  1 |      15(29)        51(27)     .        .         .        0.148
          2 |      20(36)        56(30)    1.333    0.591     3.007
          3 |      15(42)        36(19)    1.714    0.700     4.197
          4 |       9(20)        46(24)    0.584    0.227     1.502
------------------------------------------------------------------------------

. tab race low, row nokey    

           |  birth weight<2500g
      race |         0          1 |     Total
-----------+----------------------+----------
     white |        73         23 |        96 
           |     76.04      23.96 |    100.00 
-----------+----------------------+----------
     black |        15         11 |        26 
           |     57.69      42.31 |    100.00 
-----------+----------------------+----------
     other |        42         25 |        67 
           |     62.69      37.31 |    100.00 
-----------+----------------------+----------
     Total |       130         59 |       189 
           |     68.78      31.22 |    100.00 


. xi:logistic low i.race   
i.race            _Irace_1-3          (naturally coded; _Irace_1 omitted)

Logistic regression                               Number of obs   =        189
                                                  LR chi2(2)      =       5.01
                                                  Prob > chi2     =     0.0817
Log likelihood = -114.83082                       Pseudo R2       =     0.0214

------------------------------------------------------------------------------
         low | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _Irace_2 |   2.327536   1.078613     1.82   0.068     .9385073    5.772385
    _Irace_3 |   1.889234   .6571342     1.83   0.067     .9554577    3.735597
------------------------------------------------------------------------------

. unitab low , c(race)  
------------------------------------------------------------------------------
     low    |    low=1(%)      Total(%)     OR   [95% Conf. Interval]  p-value
------------+-----------------------------------------------------------------
    race  1 |      23(24)        96(51)     .        .         .        0.082
          2 |      11(42)        26(14)    2.328    0.939     5.772
          3 |      25(37)        67(35)    1.889    0.955     3.736
------------------------------------------------------------------------------

. unitab low age ht ui, c(race smoke ageq)    
------------------------------------------------------------------------------
     low    |    low=1(%)      Total(%)     OR   [95% Conf. Interval]  p-value
------------+-----------------------------------------------------------------
     age    |      59(31)       189(100)   0.950    0.893     1.011     0.105
------------+-----------------------------------------------------------------
      ht    |      59(31)       189(100)   3.365    1.021    11.088     0.046
------------+-----------------------------------------------------------------
      ui    |      59(31)       189(100)   2.578    1.139     5.834     0.023
------------+-----------------------------------------------------------------
    race  1 |      23(24)        96(51)     .        .         .        0.082
          2 |      11(42)        26(14)    2.328    0.939     5.772
          3 |      25(37)        67(35)    1.889    0.955     3.736
------------+-----------------------------------------------------------------
   smoke  0 |      29(25)       115(61)     .        .         .        0.026
          1 |      30(41)        74(39)    2.022    1.081     3.783
------------+-----------------------------------------------------------------
    ageq  1 |      15(29)        51(27)     .        .         .        0.148
          2 |      20(36)        56(30)    1.333    0.591     3.007
          3 |      15(42)        36(19)    1.714    0.700     4.197
          4 |       9(20)        46(24)    0.584    0.227     1.502
------------------------------------------------------------------------------

. unitab low age ht ui, c(race smoke ageq) l(90) f(%6.5f)   
------------------------------------------------------------------------------
     low    |    low=1(%)      Total(%)     OR   [90% Conf. Interval]  p-value
------------+-----------------------------------------------------------------
     age    |      59(31)       189(100) 0.95013  0.90214   1.00068     0.105
------------+-----------------------------------------------------------------
      ht    |      59(31)       189(100) 3.36538  1.23726   9.15396     0.046
------------+-----------------------------------------------------------------
      ui    |      59(31)       189(100) 2.57778  1.29874   5.11644     0.023
------------+-----------------------------------------------------------------
    race  1 |      23(24)        96(51)     .        .         .        0.082
          2 |      11(42)        26(14)  2.32754  1.08607   4.98812
          3 |      25(37)        67(35)  1.88923  1.06614   3.34780
------------+-----------------------------------------------------------------
   smoke  0 |      29(25)       115(61)     .        .         .        0.026
          1 |      30(41)        74(39)  2.02194  1.19518   3.42061
------------+-----------------------------------------------------------------
    ageq  1 |      15(29)        51(27)     .        .         .        0.148
          2 |      20(36)        56(30)  1.33333  0.67373   2.63871
          3 |      15(42)        36(19)  1.71429  0.80857   3.63453
          4 |       9(20)        46(24)  0.58378  0.26408   1.29051
------------------------------------------------------------------------------

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