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How do I test for the linear trend of proportions? | Stata FAQ

We present three examples for three different types of data structures. Let’s first create a sample data set. Each of the examples below will be based on some version of the same data set. It can be grouped or reshaped.

clear
set seed 12357
set obs 100
gen id = _n
gen year = mod(_n, 10) + 1
tab year
gen x = uniform()>.6

Example 1 : Testing on linear trend of proportions using the individual data set

Example 2 : Testing on linear trend of proportions using the grouped data

Example 3 : Testing on linear trend of proportions using the grouped data set in wide format

You data might be in grouped data format, but it is also wide, similar to the data listed below. You can use a Stata user-written program called ptrend to perform the test. You may have to download it from the internet and can do so by using " search ptrend " command.

preserve
contract year x, freq(freq)
reshape wide freq, i(year) j(x)
     +----------------------+
     | year   freq0   freq1 |
     |----------------------|
  1. |    1       6       4 |
  2. |    2       7       3 |
  3. |    3       4       6 |
  4. |    4       6       4 |
  5. |    5       4       6 |
     |----------------------|
  6. |    6       5       5 |
  7. |    7       6       4 |
  8. |    8       7       3 |
  9. |    9       4       6 |
 10. |   10       6       4 |
     +----------------------+
ptrend freq1 freq0 year
     +------------------------------+
     | freq1   freq0   _prop   year |
     |------------------------------|
  1. |     4       6   0.400      1 |
  2. |     3       7   0.300      2 |
  3. |     6       4   0.600      3 |
  4. |     4       6   0.400      4 |
  5. |     6       4   0.600      5 |
     |------------------------------|
  6. |     5       5   0.500      6 |
  7. |     4       6   0.400      7 |
  8. |     3       7   0.300      8 |
  9. |     6       4   0.600      9 |
 10. |     4       6   0.400     10 |
     +------------------------------+
Trend analysis for proportions
------------------------------
Regression of p = freq1/(freq1+freq0) on year:
Slope =  .00303, std. error =  .01732, Z =   0.175
Overall chi2(9) =         5.051,  pr>chi2 = 0.8299
Chi2(1) for trend =       0.031,  pr>chi2 = 0.8611
Chi2(8) for departure =   5.020,  pr>chi2 = 0.7554