Modeling Item-Level Spelling Variance in Adults: Providing Further Insights into Lexical Quality

Figures & data

Table 1. Demographic characteristics of participants.

Variable	Full sample N = 61
Age (Years)	M = 19.4 SD = 1.55
Subjective Spelling Ability Rating	M = 2.59 SD = 0.72
Sex (%)
Female	70.49%
Male	29.51%
Ethnicity (%)
Hispanic/Latino	39.34%
Non-Hispanic/Latino	60.66%
Multilingual (%)
Yes	37.70%
No	62.30%
Primarily English-speaking (%)
Yes	90.16%
No	9.84%
Race (%)
American Indian/Alaskan Native	0.00%
Asian	3.28%
Black/African American	8.19%
White	81.97%
Multiracial	6.56%

Note. M and SD are used to represent mean and standard deviation, respectively. Subjective spelling ability rating ranged on a scale from 1 to 4, with 1 being a very bad speller and 4 being a very good speller.

Figure 1. Visualization of misspellings for “assiduous” and “kaleidoscope” on target spelling task.

Note. Here the points (labels) are jittered to minimize overlapping. The jittering introduces randomness into rendering the plot. The reason for this jittering is that without it the misspelled forms would overlap at each level of x- and y- such that you could only see one misspelling, and the rest would be plotted behind it. The left panels show misspellings where the participant rated the target as familiar, and the right panels show those corresponding to unfamiliar ratings for the target. Target words were chosen because they exhibited variability in the familiarity rating across participants, where “assiduous” was only familiar to 11 participants and “kaleidoscope” was reported as being familiar to 48 participants. The origin of each plot represents the target itself, such that the distance of a given misspelling from the origin can be interpreted as the extent to which that misspelling is dissimilar from the target word either with respect to its orthographic structure (x-axis) or phonological structure (y-axis). Word labels (points) are colored based on the number of particular misspellings observed across participants. Dashed diagonals are included as a reference.

Table 2. Descriptive statistics and zero-order correlations of person & word-level features in the full sample (N = 61).

Person-Level Variable	M	SD	1	2	3	4
1. Decoding (PDE)	49.41	9.29
2. General Set for Variability	35.46	5.62	.50**
3. Target Familiarity (Total)	18.86	3.52	.44**	.66**
4. Target Spelling (Total)	8.89	4.95	.52**	.55**	.48**
Word-Level Variable
1. Length	9.44	1.30
2. Log HAL Frequency	6.32	1.67	.05
3. Number of Morphemes	2.00	0.85	.44*	−.17
4. Number of Schwas	1.48	0.50	.29	−.19	.47*
5. STPT Rating	3.74	0.80	.28	−.47*	.18	.14

Note. M and SD are used to represent mean and standard deviation, respectively. * indicates p < .05. ** indicates p < 001. PDE = Phonemic Decoding Efficiency subtest from the TOWRE-2 (Torgesen et al., 2012); HAL = Hyperspace Analogue to Language corpus; STPT = Spelling to Pronunciation Transparency.

Table 3. Difficulty ranking by number of misspellings per target spelling word (N = 25).

Word	Difficulty Ranking	N of Participants Who Misspelled Word	N of Unique Misspellings
assiduous	1	59	30
bureaucracy	2	56	32
soliloquy	3	52	40
kaleidoscope	4	52	30
charlatan	5	51	28
effeminate	6	49	23
cacophony	7	46	33
debauchery	8	46	27
aqueduct	9	46	9
colloquial	10	44	18
plagiarism	11	44	12
embarrassed	12	43	9
omniscient	13	42	16
medieval	14	40	14
nauseous	15	38	29
miscellaneous	16	38	25
boisterous	17	36	22
poignant	18	35	22
pneumonia	19	34	21
separate	20	30	2
etiquette	21	26	26
pinnacle	22	24	13
nonchalant	23	18	14
avalanche	24	10	5
tranquil	25	8	6

Note. The maximum number of individuals who could misspell a given word was 61, the total sample size.

Table 4. Fixed effects and variance estimates predicting probability of correct word spelling responses on target spelling task.

	Unconditional Model				Main Effects Model I				Main Effects Model II
Fixed effects	Est.	SE	z	p	Est.	SE	z	p	Est.	SE	z		p
Intercept	−.85	.31	−2.75	.01	−.85	.25	−3.36	<.001	−12.83	1.44	−8.89	<.001
Item-Specific Factors^a
Proportion of CSS	–	–	–	–	–	–	–	–	11.70	1.40	8.37	<.001
SfV	–	–	–	–	–	–	–	–	.86	.29	2.92	<.01
Target Familiarity									1.07	.34	3.18	<.01
Person-Level Factors^b
Decoding (PDE)	–	–	–	–	.04	.02	2.75	.01	.05	.02	3.17	<.01
SfV	–	–	–	–	.07	.03	2.07	.04	.02	.03	.59	.56
Target Familiarity	–	–	–	–	.05	.05	1.09	.28	.05	.05	.98	.33
Word-Level Factors^c
Log HAL Frequency	–	–	–	–	.13	.16	.82	.41	−.21	.20	−1.03	.30
Morphemes	–	–	–	–	−.48	.28	−1.73	.08	−.54	.35	−1.52	.13
STPT Rating	–	–	–	–	−.44	.32	−1.35	.18	−.74	.41	−1.81	.07
Intercepts	Variance				Variance		Variance Explained
Person	1.37				0.63		49.15%
Word	1.69				1.19		29.43%

Note. Est.= Parameter Estimate; SE = Standard Error; PDE = Phonemic Decoding Efficiency subtest from the TOWRE-2 (Torgesen et al., 2012); SfV = Set For Variability; CSS = Correctly Spelled Schwas; HAL = Hyperspace Analogue to Language corpus; STPT = Spelling to Pronunciation Transparency. Each of the predictors and respective estimates represent the results from predicting probability of word spelling accuracy from all variables simultaneously (i.e., in the presence of all other word- and person-level predictors in the model). ^aItem-specific factors represent item-specific performance; ^bPerson-level factors represent aggregate performance by the individual on the measure. ^cWord-level factors represent fixed characteristics of the 25 target spelling words that remain constant across individual participants.

Table 5. Exploratory interaction effects predicting probability of correct word spelling responses on target spelling task.

	Unconditional model				Exploratory Model I				Exploratory Model II
Fixed effects	Est.	SE	z	p.	Est.	SE	z	p	Est.	SE	z	p
Intercept	−.85	.31	−2.75	.01	−12.66	1.43	−8.85	<.001	−2.59	.35	−7.46	<.001
Interaction^a
PDE x STPT Rating	–	–	–	–	.01	.01	1.18	.24	.03	.01	2.76	.01
Item-Specific Factors^b	–	–	–	–
Proportion of CSS	–	–	–	–	11.52	1.38	8.33	<.001	–	–	–	–
SfV	–	–	–	–	.84	.29	2.86	<.01	.75	.24	3.17	<.01
Target Familiarity	–	–	–	–	1.07	.34	3.18	<.01	1.40	.26	5.37	<.001
Person-Level Factors^c
Decoding (PDE)	–	–	–	–	.05	.02	3.20	<.01	.05	.02	3.00	<.01
SfV	–	–	–	–	.02	.03	.62	.53	.06	.03	1.67	.09
Target Familiarity	–	–	–	–	.05	.05	.98	.32	<.01	.05	.05	.96
Word-Level Factors^d			–	–
Log HAL Frequency	–	–	–	–	−.21	.20	−1.05	.30	−.01	.15	−.08	.94
Morphemes	–	–	–	–	−.54	.35	−1.53	.13	−.40	.26	−1.55	.12
STPT Rating	–	–	–	–	−.75	.41	−1.83	.07	−.46	.31	−1.49	.14

Note. Est.= Parameter Estimate; SE = Standard Error; PDE = Phonemic Decoding Efficiency; STPT = Spelling to Pronunciation Transparency; SfV = Set for Variability; CSS = Correctly Spelled Schwas. Each of the predictors and respective estimates represent the results from predicting probability of word spelling accuracy from all variables simultaneously (i.e., in the presence of all other word- and person-level predictors in the model). ^aInteractions are between a person-level predictor and a word-level predictor for a specific spelling item response; ^bItem-specific factors represent item-specific performance; ^cPerson-level factors represent aggregate performance by the individual on the measure; ^dWord-level factors represent fixed characteristics of the 25 target spelling words that remain constant across individual participants.

Figure 2. Interaction of total decoding score and spelling-to-pronunciation transparency rating in likelihood of accuracy on target spelling task.

Note. Decoding ability and transparency rating are both mean-centered predictors with each unit away from the mean representing one standard deviation (e.g., 0.81 [red line] in the legend indicates a spelling-to-pronunciation transparency rating that is one standard deviation above the average score; -10 on the x-axis indicates a raw total score on the phonemic decoding efficiency task that is 1 standard deviation below the average raw total score).

Torgesen, J. K., Wagner, R., & Rashotte, C. (2012). Test of word reading efficiency 2. Pro-Ed.

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