Auditory Processing and Reading Disability: A Systematic Review and Meta-Analysis

Figures & data

Figure 1. PRISMA Diagram for the Present Review.

Table 1. A Priori Power Estimates from Known Extant Literature for Categorical Studies.

Analysis	Estimate (Hedges’ g)	k	Power
Frequency Discrimination	.7	46	≥.99
Duration Discrimination	.9	23	≥.99
Intensity Discrimination	.5	21	≥.99
Gap Detection	.6	19	≥.99

Figure 2a. Forest Plot of Frequency Discrimination Effect Sizes

Figure 2b. Forest Plot of Frequency Discrimination Effect Sizes, Continued from Figure 2a.

Figure 3. Forest plot of Duration Discrimination Effect Sizes.

Figure 4. Forest Plot of Intensity Discrimination Effect Sizes.

Figure 5. Forest Plot of Gap Detection Effect Sizes. Note. The 4I-2AFC used 4 stimuli and participants were told either stimulus 2 or 3 was different from the other 3.

Table 2. Magnitude of Auditory Processing Impairments in RD: Intercept-only Models.

Task Category	N	k	I^2	τ^2	Hedges' g	t	SE	df	95% CI
Frequency Discrimination	30	55	76.12	0.23	.79	7.56***	.11	27.9	[0.58 1.01]
Duration Discrimination	14	22	66.49	0.15	.80	6.12***	.13	12.5	[0.52 1.08]
Intensity Discrimination	24	34	52.39	0.10	.60	7.65***	.08	21.3	[0.44 .76]
Gap Detection^a	16	23	75.20	0.35	.80	4.89***	.16	14.8	[0.45 1.15]

Note. N = number of samples/studies; k = number of effect sizes. ***All models were significant at p < .001.

^aGap detection model is presented with an extreme outlier (Fostick et al., 2012) excluded.

Table 3. Effects of Task Design: Meta-regression Models.

Model	N	k	I^2	τ^2	A priori power	Adjusted power	g	t	SE	df	p	95% CI
Frequency	24	38	77.40	0.26	.94	.65^b
Intercept							0.73	3.20**	0.21	10.89		[0.22 1.24]
ABABA							−0.03	−0.13	0.26	6.51	.90	[−0.66 0.60]
AXB							0.25	0.94	0.27	16.75	.36	[−0.32 0.82]
Duration	13	19	70.01	0.19	.94	.10^b
Intercept							0.78	4.30**	0.18	5.89		[0.33 1.22]
AXB							0.08	0.23	0.32	10.10	.81	[−0.64 .079]
Intensity	15	21	31.36	0.04	.94	.42^c
Intercept							0.48	6.55**	0.07	11.47		[0.32 0.64]
ABABA							0.26	1.13	0.23	3.33	.33	[−0.44 0.97]
Gap Detection^a	11	17	62.85	0.21	.94	.12^b
Intercept							0.57	6.44**	0.09	6.99		[0.36 0.078]
GIN							1.04	1.82	0.57	3.81	.15	[−0.58 2.66]

Note. N = number of samples/studies; k = number of effect sizes. **All intercepts were significant at p < .01.

^a– model is presented with an extreme outlier excluded.

^b– I² used in power calculation was 75%.

^c– I² used in power calculation was 25%.

Table 4. Between- and Within-study Bias Analyses.

Model	N	k	I^2	τ^2	g	SE	t	df	p	95% CI
Within-Study Bias	63	135	76.81	0.28
Intercept					0.73	0.08	8.77*	40.79		[0.56 0.89]
Good Quality					−0.48	0.19	−2.52	3.59	.07	[−1.03 0.07]
Poor Quality					0.28	0.20	1.38	26.24	.18	[−0.14 0.69]
Between-Study Bias	63	135	75.28	0.26
Intercept					0.45	0.10	4.45*	9.61
Standard Error					2.84	0.10	2.85	2.84	.03^a	[−0.44 6.11]

Note. N = number of studies; k = number of effect sizes. *All intercepts were significant at p < .05.

^aOne-tailed test was used, as is customary for Egger’s Regression.