Misty: A Collection of Statistical and Psychometric Functions

Misty is a collection of miscellaneous functions for data analysis created by Takuya Yanagida. The functions cover data handling, descriptive statistics, missing data analysis, multilevel modeling, item analysis, and statistical testing. It also includes utilities to interact with the 'Blimp' and 'Mplus' statistical software.

Use Cases

• Perform multilevel confirmatory factor analysis based on functions for multilevel data.
• Conduct missing data pattern analysis and Little's MCAR test based on missing data functions.
• Calculate coefficient alpha and omega for scale reliability based on item analysis functions.
• Run dominance analysis and collinearity diagnostics based on statistical analysis functions.
• Center data using grand-mean and group-mean methods based on data handling functions.

Strengths

• Functions cover seven distinct methodological areas, including multilevel modeling and missing data analysis.
• The description explicitly lists interaction capabilities with 'Blimp' and 'Mplus' software.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Takuya Yanagida