Comparing Direct Measurement & Simulation Results: Paired t Test?

[Lisa!]

If we measure a quantity with 2 different tools(once by direct measurements and the other time through simulation), is it true if we compare these 2 results together by using paired t test?
Does it makes sense ?
For example we want to measure the aborbed dose of a patient, so once we measure it directly by using TLD(some kind of detector) and the other time we measure it through simulation by MCNP method. Now we want to see if these results are significantly different from each other or they're in a good agreement with each other, can we use paired t test for that purpose or is it wrong?

Thanks
PS1: Feel free to move it to the right forum and sorry if I've not posted it in the right place.
PS2: Please let me know if I've not clearly stated my question.

 

[EnumaElish]

You can use a paired t-test provided you are comparing outcomes from two random variables each of which is normally distributed, or can be transformed to normal through a weighting algorithm. In the latter case you need to perform a weighted t test. In case of non-random samples (e.g. you tested every third patient at 2pm every other day) there may be a sampling bias.

 

[statdad]

If we measure a quantity with 2 different tools(once by direct measurements and the other time through simulation), is it true if we compare these 2 results together by using paired t test?

Unless, in your two sets of data, the two items in the first row, the two in the second row, and so on, are collected under similar conditions (from same person, before and after, or something else) a paired t-test is not appropriate.

Does it makes sense ?
For example we want to measure the aborbed dose of a patient, so once we measure it directly by using TLD(some kind of detector) and the other time we measure it through simulation by MCNP method. Now we want to see if these results are significantly different from each other or they're in a good agreement with each other, can we use paired t test for that purpose or is it wrong?

This seems to meet the criterion for the paired test. Remember that a paired t-test is simply a regular t-test applied to the differences, so you should make sure the differences of the data are reasonably symmetric and have few (preferably no) outliers, as t-tests are notoriously sensitive to departures from normality.
Thanks
PS1: Feel free to move it to the right forum and sorry if I've not posted it in the right place.
PS2: Please let me know if I've not clearly stated my question.[/QUOTE]

 

[Lisa!]

Thank you, guys!
Your posts were really helpful...

Unless, in your two sets of data, the two items in the first row, the two in the second row, and so on, are collected under similar conditions (from same person, before and after, or something else) a paired t-test is not appropriate.

This seems to meet the criterion for the paired test. Remember that a paired t-test is simply a regular t-test applied to the differences, so you should make sure the differences of the data are reasonably symmetric and have few (preferably no) outliers, as t-tests are notoriously sensitive to departures from normality.

Nice explanation!