Group work - field test

As part of your research investigating the effect of a multidisciplinary intervention for patients with chronic whiplash associated disorder (WAD) in patients seen in primary and secondary sectors of the Danish health care system, you are continuing your work on the Neck Disability Index (NDI).

Recall from the introductory course that the NDI has 10 items, each item has 6 response options, and the scale range is 0-100 (high score equals high disability). It is based on a reflective model.

(You can view the NDI in full by clicking here: Neck Disability Index)


You have decided to perform a field test procedure on the NDI to see how the data structure looks like and how the items are performing.

For this you need to download the dataset: (unpack the zip-file).

You want to look at the properties listed below. Try to solve the questions using Stata without looking at the hints. However, if you run into trouble, please use them.

1. Item characteristics

1.1 Item scores

Look at the median, mean, and missings for each item.


Use the fsum command at baseline with the relevant stats for each item.

ssc install fsum //Installing the fsum ado file in Stata's command window


1.1 Describe your findings and discuss what they mean.

1.2 Item distribution

Look at how the scores of each item is distributed across the answer categories.


Use the tabulate command with the options missing details at baseline for each item.


1.2 Describe your findings and discuss what they mean.

2. Reproducibility

2.1 Internal consistency

Calculate the internal consistency (both overall and at item level).


Use the alpha command with the options std item at baseline for all item.


2.1.1 Describe your findings and discuss what they mean.

2.1.2 Should we remove an item? If so, which one(s)?

If you believe one or more items should be removed, please run the new analysis.


Use the same command as before without the poorly fitting item.


2.1.3 Describe your findings of the new internal consistency analysis and discuss what they mean.

2.2 Reliability

Please determine the reliability (ICC-values) at item level.


Use the icc command (in older versions of Stata, use the icc23 command) for each item. The forvalues command can be used to make the sytax shorter.

icc23 //Stata<12: Install it by typing - scc install icc23 - in Stata's command window

You can use the forvalues command to make the syntax shorter.

forvalues i = 1(1)10 {
icc n`i' idnr bafu if stable==2, absolute
quietly display as text "The ICC for Question `i' = " _col(40) as result %5.4f r(icc_i)
quietly display as text "No of stable pts for Question `i' = " _col(40) r(N_target)

The code above calculates an ICC for each item and displays the ICC and the number of stable patients for each item. If you want to see the ICC output, you can remove ‘quietly’.


2.2 Describe your findings and discuss what they mean.

3. Floor and ceiling effect

3.1 Conventional method

Calculate the floor and ceiling effect using the ‘conventional’ method.


Use the tabulate command to find the floor and ceiling effects.


3.1 Describe your findings and discuss what they mean.

3.2 Scale width method

Calculate the floor and ceiling effect using the ‘scale width method’.


Use the concord command. Install the command by typing scc install concord. The graph in the code is for illustration of the LOA and exporting it can be omitted.

Then use the following code:

sort idnr
keep idnr bafu stable NDI10

reshape wide NDI10 stable, i(idnr) j(bafu)
drop stable1
order idnr stable2 NDI10*

keep if stable==2

concord NDI*, loa(lopts(lp(dash..)))
graph export "B_A_plot, all pts.wmf", replace

NB: do not save the dataset after running this code as it will change the dataset. If you need a clean dataset, please download it from the webpage.

You can use the concord output to find the measurement error, and then find the % of patients who fall within measurement error at each end of the scale.


3.2 Describe your findings and discuss what they mean.