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The non-normed fit index (NNFI; also known as the Tucker–Lewis index, as it was built on an index formed by Tucker and Lewis, in 1973) resolves some of the issues of negative bias, though NNFI values may sometimes fall beyond the 0 to 1 range.
There are several relative fit indices, including Bollen’s Incremental Fit Index (IFI, also called BL89 or ∆. 2), the Tucker-Lewis Index [TLI, Bentler-Bonett Nonnormed Fit Index (NNFI or BBNFI), or ρ. 2], and the Bentler-Bonett Normed Fit Index (NFI). 3. Most of these fit indices are computed by using ratios of
Jun 4, 2018 · In structural equation modeling, application of the root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker–Lewis index (TLI) highly relies on the conventional cutoff values developed under normal-theory maximum likelihood (ML) with continuous data.
- Yan Xia, Yanyun Yang
- 2019
Jun 5, 2020 · The Tucker-Lewis index (also called the non-normed fit index or NNFI), another incremental fit index, does have such a penalty. Let χ 2 /df be the ratio of chi square to its degrees of freedom , and the TLI is computed as follows:
Mplus lists another fit statistic along with the CFI called the TLI Tucker Lewis Index which also ranges between 0 and 1 with values greater than 0.90 indicating good fit. If the CFI and TLI are less than one, the CFI is always greater than the TLI.
Jun 29, 2018 · This study investigated the effect the number of observed variables ( p) has on three structural equation modeling indices: the comparative fit index (CFI), the Tucker–Lewis index (TLI), and the root mean square error of approximation (RMSEA).
An NFI of 0.95, indicates the model of interest improves the fit by 95\ NNFI (also called the Tucker Lewis index; TLI) is preferable for smaller samples. They should be > .90 (Byrne, 1994; "byrne1994" ) or > .95 (Schumacker & Lomax, 2004; "schumacker2004" ).
