Specific to other Project Implicit researchers

Formats demographics variables from Project Implicit (.sas)

Shows how to create labels for character and numeric variables and use them to label output from PROCedures. Creates and accesses common directory for saved formats (including one for IAT subexclusion criteria). Also contains an example of how to use SAS's default country/continent formats (the labels stored in SASHELP.MAPFMTS, poorly-documented in SAS) to label country codes, which are 99% standard ISO-2 codes.

Documented Cleaning Script for use with the data files accessed via the RDE/Virtual Lab (.sas)

For now, useful only to those with accounts on the Project Implicit wiki (or the RDE) because it is specific to our database's structure and formatting (though anyone may download it). For collaborators, this script documents how to clean, transpose, and merge (for substantive analysis) the standard datafiles available through Project Implicit's RDE. When transposing, it can optionally obtain some useful information (time spent on a task, sequence of implicit/explicit/other tasks within the study, etc.).For the IAT, it cleans, reverse-codes, checks for problem participants/trials, and the like in preparation for substantive analysis. Contact me for the latest version of this script.

SAS: General Use

Principal factor analysis, bootstrapping eigen cut-offs (.sas and .R)

Conducts PFA in SAS, then uses R to estimate eigen value cut-offs. See Russell (2002, PSPB) for details, but in short, this uses bootstrap estimation to calculate the average “null” eigen values (e.g., the null condition of no relationship among the variables) after simulating factor analysis within 100 randomly-generated datasets with your dimensions. See DataVerse supplement to Lindner & Nosek (2009) for an example of the figure and a write-up of all results.

Macro for dataset management - Range of date(time) and ID values for a given variable (.sas)

For a large dataset with many variables that appear during different time periods. You specify a variable, the macro determines the first and last values of the (a) observation/user ID and (b) date/datetime variable (specified by you). Prints only the variable name and the formatted beginning and ending duration values of user_ID and the date variable.

Macro for dataset management - Dynamically generate a monthly tabulated report of traffic/participation/etc. (.sas)

Given a datetime value, tabulates a report for the proceeding full month periods (specified by user). To do so, it dynamically creates a datetime format for the specified number of months, so datetime values within a month are consolidated. A tabular report for a given (formatted) row-variable (specified by user) is generated, with monthly traffic in the columns.

Datetime difference scores, graphically exploring the results (.sas)

For datasets with one row per task begun by a given participant, with a column indicating the time begun as a SAS datetime variable. Calculates the time spent on given task(s), as a difference score of the task commencement and commencement of the next task, before transposing the file for a datafile with one line/row per participant. Formats the difference score in an understandable time format. Graphically represents (via histograms) the results, with understandable time formatting.

Code Snippets (more coming soon)

Creates a custom datetime picture format that Google Docs recognizes (.sas)