Amy Liang
Biographic Data
| ID | 9218107 |
|---|---|
| NAME | Amy Liang |
| GIVEN NAMES | Amy |
| FAMILY NAME | Liang |
| SIGNATURE | LIANG A |
| AFFILIATIONS | Vanderbilt University |
| VERIFIED | No |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Parceling to Lower Indicator-to-Sample-Size Ratio? Instead Try Correcting Your SEM Chi-Square for High p and Modest N to Obtain a Nominal Type I Error Rate Without Parcel-Allocation Variability
Parceling is routinely recommended to SEM researchers with many items (high p) and modest N in order to “lower indicator-to-sample-size ratio.” Here we show that this directive is a roundabout response to address chi-square distortion at high p and modest N, which in turn leads to egregiously inflated Type I error for the item-level model’s chi-square test of absolute fit. We explain, demonstrate, and provide software to implement two more-direct…
No prominent works on this page.
Parceling to Lower Indicator-to-Sample-Size Ratio? Instead Try Correcting Your SEM Chi-Square for High p and Modest N to Obtain a Nominal Type I Error Rate Without Parcel-Allocation Variability
Parceling is routinely recommended to SEM researchers with many items (high p) and modest N in order to “lower indicator-to-sample-size ratio.” Here we show that this directive is a roundabout response to address chi-square distortion at high p and modest N, which in turn leads to egregiously inflated Type I error for the item-level model’s chi-square test of absolute fit. We explain, demonstrate, and provide software to implement two more-direct…
Electron and X-Ray Spectroscopy Techniques (1 work) · Meta-analysis and systematic reviews (1 work) · Population (1 work) · SAS software applications and methods (1 work) · Statistical analysis (1 work) · Type I and type II errors (1 work)