UNISTAT - the ultimate Excel statistics add-in

Poisson Regression in Excel with Unistat

The Unistat statistics add-in extends Excel with Poisson Regression capabilities.

Further documentation is available at section 7.2.8 of the manual, Poisson Regression.

Sample output

Here we provide annotated example report output from the Unistat Excel statistics add-in for data analysis.

Poisson Regression

Regression Results

Valid Number of Cases: 22, 0 Omitted
Dependent Variable: Number of cancers
Exposure: Subject-years

CoefficientStandard ErrorWald StatisticSignificanceLower 95%Upper 95%
Constant-9.3284 0.2086 1999.7803 0.0000-9.7372-8.9195
Status = Non-veteran 0.0035 0.0555 0.0040 0.9493-0.1052 0.1123
Age group = 25-29 0.6793 0.2325 8.5373 0.0035 0.2236 1.1350
30-34 1.3711 0.2177 39.6626 0.0000 0.9444 1.7978
35-39 1.9396 0.2121 83.6581 0.0000 1.5240 2.3553
40-44 2.0343 0.2161 88.6203 0.0000 1.6108 2.4579
45-49 2.7266 0.2222 150.5415 0.0000 2.2910 3.1621
50-54 3.2029 0.2206 210.7122 0.0000 2.7704 3.6353
55-59 3.7162 0.2178 291.1925 0.0000 3.2894 4.1430
60-64 4.0927 0.2177 353.4848 0.0000 3.6660 4.5193
65-69 4.2362 0.2242 356.9375 0.0000 3.7967 4.6757
70- 4.3637 0.2274 368.3264 0.0000 3.9181 4.8094

-2 Log likelihood:
Initial Model 2199.7137
Final Model 132.0133
Likelihood Ratio Statistic:
Chi-Square Statistic 2067.7004
Degrees of Freedom 11
Right-Tail Probability 0.0000
Goodness of Fit:
Chi-Square Statistic 5.2166
Degrees of Freedom 9
Right-Tail Probability 0.8150

Incidence Rate Ratio

Incidence Rate RatioStandard ErrorLower 95%Upper 95%
Status = Non-veteran 1.0035 0.0557 0.9001 1.1188
Age group = 25-29 1.9725 0.4586 1.2506 3.1111
30-34 3.9396 0.8577 2.5712 6.0363
35-39 6.9561 1.4751 4.5905 10.5408
40-44 7.6471 1.6525 5.0067 11.6799
45-49 15.2801 3.3956 9.8849 23.6201
50-54 24.6031 5.4286 15.9653 37.9144
55-59 41.1074 8.9521 26.8256 62.9926
60-64 59.9000 13.0391 39.0963 91.7736
65-69 69.1453 15.5040 44.5557 107.3055
70- 78.5486 17.8599 50.3034 122.6533

Correlation Matrix of Regression Coefficients

ConstantStatus = Non-veteranAge group = 25-2930-3435-3940-4445-4950-54
Constant 1.0000-0.2060-0.8648-0.9241-0.9499-0.9362-0.9098-0.9133
Status = Non-veteran-0.2060 1.0000 0.0274 0.0319 0.0387 0.0575 0.0532 0.0388
Age group = 25-29-0.8648 0.0274 1.0000 0.8241 0.8462 0.8309 0.8079 0.8133
30-34-0.9241 0.0319 0.8241 1.0000 0.9037 0.8875 0.8629 0.8686
35-39-0.9499 0.0387 0.8462 0.9037 1.0000 0.9115 0.8862 0.8920
40-44-0.9362 0.0575 0.8309 0.8875 0.9115 1.0000 0.8707 0.8761
45-49-0.9098 0.0532 0.8079 0.8629 0.8862 0.8707 1.0000 0.8518
50-54-0.9133 0.0388 0.8133 0.8686 0.8920 0.8761 0.8518 1.0000
55-59-0.9205 0.0159 0.8234 0.8793 0.9028 0.8863 0.8618 0.8678
60-64-0.9156-0.0096 0.8230 0.8789 0.9022 0.8852 0.8608 0.8671
65-69-0.8836-0.0353 0.7983 0.8524 0.8749 0.8579 0.8343 0.8408
70--0.8681-0.0504 0.7868 0.8401 0.8622 0.8451 0.8220 0.8286
55-5960-6465-6970-
Constant-0.9205-0.9156-0.8836-0.8681
Status = Non-veteran 0.0159-0.0096-0.0353-0.0504
Age group = 25-29 0.8234 0.8230 0.7983 0.7868
30-34 0.8793 0.8789 0.8524 0.8401
35-39 0.9028 0.9022 0.8749 0.8622
40-44 0.8863 0.8852 0.8579 0.8451
45-49 0.8618 0.8608 0.8343 0.8220
50-54 0.8678 0.8671 0.8408 0.8286
55-59 1.0000 0.8788 0.8527 0.8407
60-64 0.8788 1.0000 0.8540 0.8423
65-69 0.8527 0.8540 1.0000 0.8190
70- 0.8407 0.8423 0.8190 1.0000

Covariance Matrix of Regression Coefficients

ConstantStatus = Non-veteranAge group = 25-2930-3435-3940-4445-4950-54
Constant 0.0435-0.0024-0.0419-0.0420-0.0420-0.0422-0.0422-0.0420
Status = Non-veteran-0.0024 0.0031 0.0004 0.0004 0.0005 0.0007 0.0007 0.0005
Age group = 25-29-0.0419 0.0004 0.0541 0.0417 0.0417 0.0417 0.0417 0.0417
30-34-0.0420 0.0004 0.0417 0.0474 0.0417 0.0418 0.0417 0.0417
35-39-0.0420 0.0005 0.0417 0.0417 0.0450 0.0418 0.0418 0.0417
40-44-0.0422 0.0007 0.0417 0.0418 0.0418 0.0467 0.0418 0.0418
45-49-0.0422 0.0007 0.0417 0.0417 0.0418 0.0418 0.0494 0.0418
50-54-0.0420 0.0005 0.0417 0.0417 0.0417 0.0418 0.0418 0.0487
55-59-0.0418 0.0002 0.0417 0.0417 0.0417 0.0417 0.0417 0.0417
60-64-0.0416-0.0001 0.0417 0.0417 0.0416 0.0416 0.0416 0.0416
65-69-0.0413-0.0004 0.0416 0.0416 0.0416 0.0416 0.0416 0.0416
70--0.0412-0.0006 0.0416 0.0416 0.0416 0.0415 0.0415 0.0416
55-5960-6465-6970-
Constant-0.0418-0.0416-0.0413-0.0412
Status = Non-veteran 0.0002-0.0001-0.0004-0.0006
Age group = 25-29 0.0417 0.0417 0.0416 0.0416
30-34 0.0417 0.0417 0.0416 0.0416
35-39 0.0417 0.0416 0.0416 0.0416
40-44 0.0417 0.0416 0.0416 0.0415
45-49 0.0417 0.0416 0.0416 0.0415
50-54 0.0417 0.0416 0.0416 0.0416
55-59 0.0474 0.0417 0.0416 0.0416
60-64 0.0417 0.0474 0.0417 0.0417
65-69 0.0416 0.0417 0.0503 0.0418
70- 0.0416 0.0417 0.0418 0.0517

Actual and Fitted Values

RowActual *Fitted +
1.9057                                              193.7020
1 6.0000 5.4067
 *
2 21.0000 27.5518
      * +
3 54.0000 61.6656
                * +
4 118.0000 115.2981
                                   +*
5 97.0000 92.0660
                            +*
6 58.0000 57.8741
                 *
7 56.0000 54.6629
                +*
8 54.0000 50.0844
               +*
9 34.0000 32.8068
          *
10 9.0000 9.6781
  *
11 2.0000 1.9057
*
12 18.0000 18.5933
     *
13 60.0000 53.4481
                + *
14 122.0000 114.3345
                                   + *
15 191.0000 193.7020
                                                          *+
16 108.0000 112.9340
                                 *+
17 74.0000 74.1259
                      *
18 88.0000 89.3372
                          *+
19 120.0000 123.9157
                                    * +
20 141.0000 142.1933
                                           *
21 108.0000 107.3219
                                +*
22 99.0000 99.0944
                              *

Residuals

RowResiduals
-7.6656                                               7.6656
1 0.5933
                                *
2-6.5518
    *
3-7.6656
*
4 2.7019
                                        *
5 4.9340
                                                *
6 0.1259
                              *
7 1.3371
                                   *
8 3.9156
                                             *
9 1.1932
                                  *
10-0.6781
                           *
11 0.0943
                              *
12-0.5933
                           *
13 6.5519
                                                       *
14 7.6655
                                                           *
15-2.7020
                   *
16-4.9340
           *
17-0.1259
                             *
18-1.3372
                        *
19-3.9157
              *
20-1.1933
                         *
21 0.6781
                                *
22-0.0944
                             *

Case (Diagnostic) Statistics

RowFitted ValuesStandard Error of FittedLower 95%Upper 95%DevianceResidualsStandardised Residuals
1 5.4067 0.2086 4.9979 5.8156 0.0628 0.5933 0.2551
2 27.5518 0.1170 27.3225 27.7811 1.6987-6.5518-1.2482
3 61.6656 0.0836 61.5018 61.8293 0.9950-7.6656-0.9762
4 115.2981 0.0667 115.1674 115.4288 0.0628 2.7019 0.2516
5 92.0660 0.0762 91.9166 92.2154 0.2598 4.9340 0.5142
6 57.8741 0.0924 57.6929 58.0553 0.0003 0.1259 0.0165
7 54.6629 0.0902 54.4862 54.8396 0.0324 1.3371 0.1809
8 50.0844 0.0855 49.9168 50.2519 0.2984 3.9156 0.5533
9 32.8068 0.0880 32.6343 32.9793 0.0429 1.1932 0.2083
10 9.6781 0.1055 9.4712 9.8849 0.0487-0.6781-0.2180
11 1.9057 0.1134 1.6834 2.1280 0.0046 0.0943 0.0683
12 18.5933 0.2045 18.1925 18.9941 0.0191-0.5933-0.1376
13 53.4481 0.1127 53.2272 53.6690 0.7722 6.5519 0.8962
14 114.3345 0.0778 114.1819 114.4871 0.5028 7.6655 0.7169
15 193.7020 0.0605 193.5833 193.8206 0.0379-2.7020-0.1941
16 112.9340 0.0742 112.7887 113.0793 0.2188-4.9340-0.4643
17 74.1259 0.0904 73.9488 74.3030 0.0002-0.1259-0.0146
18 89.3372 0.0860 89.1687 89.5056 0.0201-1.3372-0.1415
19 123.9157 0.0775 123.7638 124.0675 0.1251-3.9157-0.3518
20 142.1933 0.0763 142.0437 142.3428 0.0100-1.1933-0.1001
21 107.3219 0.0926 107.1405 107.5034 0.0043 0.6781 0.0655
22 99.0944 0.0995 98.8993 99.2894 0.0001-0.0944-0.0095

Poisson Regression

Poisson Regression


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