Hi all, Interesting disccussion here.

2. The suggestion:

"SUGGESTION: Would it not be possible for Analysis to assign a standard valid value (e.g. 01/01/1900) to any invalid dates it comes across during the read process. "

Will be used in the next build of analysis, since it is very easy to implement. Obviously with a message to the user. I think this can be done in 5 minutes of work time in the programming, whereas the optimal solution of showing variable/field name and record is a large job - could be 1-2 days of work, since the function controlling the date value is not knowing neither the name of the field nor the record. But I will add the issue to the work plan for a solution at some point.

In my view the problem with that solution is that if Analysis automatically changes all "invalid" dates to any standard missing value, it can be a problem if the user saves the changes in a new data file and deletes the old one. The message for the users should be VERY CLEAR.

I would just like to clarify my suggestion re "excluded" and "deleted" records. The issue is not about whether one can control reading deleted records or not (as Jens' response implies). My point was that if one is not aware that records have been deleted, it would be more informative on reading the dataset in Analysis if the message specifically states that x records have been deleted (and are therefore excluded). Using the word "excluded" suggests that Analysis has a problem with some values and therefore has excluded the records. One could spend quite some time trying to identify the problem before realising that these are merely records that have been deleted.

Maybe we can use a text similar to the one used by EpiInfo for Windows: "#### records loaded (deleted records excluded/included)" Still it makes no senese to display 100 times the same message saying that a record was excluded because of an invalide date if the user can not do anything. In my view one solution can be display, in adition to the previous message, another message saying:

"#### records excluded because of quality checking with dates(or other reasons). TIP: sort ascending your data in any date variable and browse them to detect the problems"

Pedro Arias