Application of Ideal Binary Masking to Disordered Speech: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Application of Ideal Binary Masking to Disordered Speech (NCT05244603), a randomized na study. The primary outcome is Percent Correct Speech Intelligibility.

2. Clinical Question

The study concerns whether an ideal binary masking approach has a potential role in addressing speech-in-noise difficulties for listeners understanding dysarthric speech, and reports speech-intelligibility results for listeners with normal hearing and listeners with hearing loss. The registry describes dysarthria and hearing loss as communication disorders that can reduce speech intelligibility, with background noise adding a challenge. Its stated project aim is proof-of-concept work intended to inform future evaluation; the posted primary result, however, is a comparison between the two hearing-status groups.

The recorded mean was 69.0 percentage points in the Normal Hearing group and 63.0 in the Hearing Impaired group. The posted mean difference, defined as Hearing Impaired compared with Normal Hearing, was -6.0 percentage points, with a confidence interval from -10.79 to -1.214. These results describe the recorded group comparison. They do not, by themselves, establish the effect of ideal binary masking, because the posted comparison is not an explicit contrast between mask conditions.

3. Trial Design

The registry describes a completed, randomized, unmasked, parallel study sponsored by Utah State University. Enrollment was 435. The record lists the study start as 2021-12-01 and primary completion as 2023-12-01. It identifies the conditions as sensorineural hearing loss and dysarthria, and lists ideal binary mask as a behavioral intervention.

The posted arms are titled Normal Hearing and Hearing Impaired. Their descriptions identify listeners with normal hearing and listeners with hearing loss, respectively. The primary outcome population is described as including both types of listeners. The posted results show 422.0 participants in the Normal Hearing group and 13.0 in the Hearing Impaired group. These are markedly unequal group sizes, so the estimate for the smaller group is based on substantially fewer participants.

Although the registry labels allocation as randomized and the model as parallel, it does not explain what was randomized, how assignment was carried out, or how that assignment relates to hearing status and the listed masking intervention. The arm descriptions identify hearing-status groups rather than distinct mask conditions. The record also does not report the original design assumptions, the planned sample-size justification, or a detailed protocol in the information. The trial’s phase is listed as not applicable.

The study’s stated purpose was to investigate the potential application of an established signal-processing technique to understanding dysarthric speech in noise, with the aim of demonstrating proof of concept and informing a larger evaluation. That stated purpose provides context, but the posted primary result is a group comparison in percent-correct speech intelligibility. There are no posted statistical analyses listed in the registry record, and no secondary outcomes are posted.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Listeners with normal hearing and listeners with hearing loss

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Percent Correct Speech Intelligibility, measured over One hour.

The primary endpoint is Percent Correct Speech Intelligibility. It measures the percentage of keywords a participant correctly identifies from processed speech stimuli. Participants were presented with phrases containing several words, reported what they heard, and the correctly reported words were counted and converted to a percent-correct score. The recorded timeframe is one hour.

This endpoint turns performance on the speech-identification task into a continuous measure that can be summarized as a mean for each group. It focuses on whether listeners accurately recover keywords from the presented phrases, rather than on a broader clinical outcome. The registry describes the result as a mean and reports its dispersion as a standard error.

In this study, a higher percent-correct score indicates that a greater share of the keywords in the task were correctly reported. The measure is relevant to the study’s stated focus on speech intelligibility, especially in the context of disordered speech and background noise. The registry summary describes the broader rationale but the posted endpoint results do not separately identify performance by speech type, noise condition, or mask condition. Those details are not reported in the registry record, so the mean scores should be read as the posted group-level results for the defined endpoint, not as evidence about every task condition or about a specific masking contrast.

7. Results Posted in the Registry

• Hearing Impaired: mean 63.00 versus 69.00 on control; difference -6.00 (95% CI -10.79 to -1.21), standardized effect d = -0.28; z-test p = 0.014.

8. Statistical Interpretation

9. Statistical Methods Explained

The posted primary outcome is continuous: each participant’s score is the percent of keywords correctly reported, and the registry summarizes the group results as means. The comparison reports a mean difference between the Hearing Impaired and Normal Hearing groups. A mean difference expresses the separation between group averages in the endpoint’s original units, here percentage points. Its sign depends on which group is subtracted from which; the posted comparison is Hearing Impaired relative to Normal Hearing, so the negative estimate indicates a lower recorded mean in the first-named group.

What does the standard error describe?

The registry reports standard errors of 1.06 for the Normal Hearing mean and 2.2 for the Hearing Impaired mean. In general, a standard error describes the statistical uncertainty in an estimated quantity, such as a sample mean, rather than the spread of individual participant scores. It is affected by both the variability of the observations and the number of observations contributing to the estimate. A smaller standard error generally indicates a more precisely estimated mean, while a larger one indicates more sampling uncertainty. It should not be interpreted as meaning that individual scores lie close to the group mean.

The standard errors differ between the groups, and the participant counts differ substantially as well. This makes it important to read the group summaries alongside their sample sizes and the confidence interval for the difference. A group mean on its own does not show how much participants’ scores varied, and the standard error is not a substitute for the full distribution of scores. The registry does not post a standard deviation for each group or a plot of individual endpoint values in the record.

What does the confidence interval add?

A confidence interval gives a range of estimates that are compatible with the observed data and the procedure’s assumptions. It conveys uncertainty around the estimated mean difference, rather than giving a guarantee that the true difference lies within the particular interval. For this comparison, the posted interval extends from -10.79 to -1.214. The interval does not include zero, which is consistent with the reported unadjusted p value of 0.014 under a conventional test of no difference. The registry record does not identify the exact model, test, or method used to construct the interval, so interpretation should not assume a particular procedure beyond what is posted.

How should the p value be understood?

In general, a p value measures how unusual data at least as incompatible with a specified null hypothesis would be if that hypothesis and the statistical model were correct. It is not a measure of the probability that a finding is due to chance, and it does not tell readers whether a difference matters in practice. The posted p value is unadjusted. The record lists no statistical analyses and does not report whether this comparison was prespecified in a detailed analysis plan. No multiplicity adjustment is reported.

The p value and confidence interval are related ways of describing uncertainty about the group difference, but neither tells whether the observed contrast is caused by an intervention. In this case, the groups are identified by hearing status, while the intervention is listed separately as ideal binary mask. The record does not clarify the relationship between randomized assignment, mask exposure, and the posted group comparison. Statistical significance for this group contrast cannot resolve that design ambiguity.

Why do imbalance and dispersion matter?

The posted groups are very unequal in size. In general, an estimate from a small group tends to carry more sampling uncertainty than an estimate from a larger group, all else being equal. The reported standard errors and interval provide some information about precision, but they cannot reveal whether the groups differ in other relevant characteristics or whether the analysis accounted for such differences. The registry does not report covariate adjustment or a detailed model.

Over-dispersion is a general concern when the observed variability is greater than a chosen model expects. If a model underestimates variability, standard errors may be too small and confidence intervals too narrow. This is a general statistical consideration, not a finding about this trial: the registry does not report a dispersion assessment or enough model detail to determine whether this issue was evaluated. Because the endpoint is a percentage, scores may also have limits, but the posted record does not provide the score distributions or modeling details needed to assess how those features were handled.

The posted values are the registry’s reported results. The calculated comparison and its interval are presented as the registry result rather than as an independently reconstructed analysis. No discrepancy is flagged in the record. There are no posted secondary outcome analyses, and the number of analyses is listed as zero. That absence limits how much can be said about robustness across outcomes, alternative models, or subgroup definitions.

10. Confidence Intervals and Precision

The mean difference is reported as -6.0 percentage points for Hearing Impaired compared with Normal Hearing. Its confidence interval ranges from -10.79 to -1.214. This interval is the central description of precision for the between-group estimate: it shows that the point estimate is not exact and that values across a range remain compatible with the data and method. The interval is entirely below zero, while its width also indicates that the estimate is not a single fixed value.

Precision should be considered alongside the group sizes and standard errors. The Normal Hearing group includes 422.0 participants, with a standard error of 1.06; the Hearing Impaired group includes 13.0 participants, with a standard error of 2.2. The smaller group’s mean therefore has greater reported sampling uncertainty. The confidence interval for the difference incorporates uncertainty in the comparison, but the record does not describe the method used to construct it or provide enough detail to assess all modeling assumptions.

A confidence interval is not a range that contains every participant’s score, nor does it show the distribution of scores. It also does not capture uncertainties arising from unreported design details, possible selection processes, or questions about how the intervention relates to the hearing-status comparison. The interval pertains to the specific posted mean difference and should not be generalized to unreported task conditions or treated as an intervention-effect interval.

The p value of 0.014 is consistent with the interval’s exclusion of zero, but it does not make the estimate more precise or resolve the interpretation of the study design. Precision concerns how tightly the data estimate a quantity; causal attribution and generalizability require additional design and analysis information that is not reported in the registry record.

11. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The sample-size table and its accompanying curve are planning illustrations based on the observed group difference, not the trial’s original enrollment design. The figures are participants per arm, not total events. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set at the stated fraction of the observed effect. The trial’s own original design assumptions are not reported in the registry record.

For each effect size shown, the 80% power column gives the illustrative number of participants per arm for a design with an 80% chance of detecting an effect of that size under the stated assumptions, if the effect exists and the assumptions hold. The 90% power column gives the corresponding per-arm planning figure for a design with a 90% chance. These are prospective planning quantities, not descriptions of what happened in the completed study. They are not observed power.

The table includes planning for 100% of the observed effect, planning for 75% of the observed effect, and planning for 50% of the observed effect. For 100% of the observed effect, the illustrations are 202 participants per arm for 80% power and 271 for 90% power. For 75% of the observed effect, they are 359 and 481 participants per arm, respectively. For 50% of the observed effect, they are 808 and 1,081 participants per arm. The curve provides a visual representation of this planning relationship.

The general pattern is that smaller effects are harder to distinguish from random variation, so planning to detect a smaller effect requires more participants under the same assumptions. These figures are illustrations based on the observed estimate and specified assumptions; they do not establish that the original study was designed with these targets or that its actual design had a particular probability of success.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -6.000; pooled standard deviation σ = 21.512.
2. n = 2 × (1.96 + 0.842)² × 21.512² / -6.000² = 201.8, rounded up to 202 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -6                      # observed difference in means
sigma <- 21.5119099726116                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(5244603)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 202 (80% power), 271 (90% power)
 75% of observed effect: n per arm = 359 (80% power), 481 (90% power)
 50% of observed effect: n per arm = 808 (80% power), 1,081 (90% power)
power.t.test: 202.8 
Simulated power at n = 202 per arm: 0.799 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome measure and no posted secondary outcome measures. It lists zero statistical analyses. The primary result includes an unadjusted p value of 0.014, but the record does not report a full statistical analysis plan or say whether any other comparisons were planned or conducted. It also does not report a multiplicity adjustment.

In general, multiplicity arises when several outcomes, groups, time points, or statistical tests are examined. When many tests are performed, the chance of observing at least one apparently unusual result can increase. Adjustment methods are sometimes used to account for that issue, but whether an adjustment is appropriate depends on the planned questions and analysis strategy. Because the registry record does not report the analysis plan or the full set of analyses, it is not possible to assess the extent of any multiplicity or how it was handled. The posted p value should therefore be read as unadjusted, not as evidence that every possible analysis was considered.

Missing-data handling is also not reported in the registry record. The posted group counts total the enrolled participants, but the record does not explain whether every enrolled participant contributed an endpoint score, whether any observations were excluded, or how missing endpoint data were treated. The enrollment figure alone cannot answer those questions. No imputation method, complete-case rule, or sensitivity analysis is reported.

The analysis population is not described in detail. The registry does not say whether the result is based on all randomized participants, all participants with usable endpoint data, or another defined set. It does not provide a participant flow account or explain exclusions after enrollment. These omissions limit assessment of how the posted comparison relates to the original randomized design and whether the analyzed groups preserve any intended assignment structure.

These missing details do not change the arithmetic of the posted result, but they constrain interpretation. In particular, the registry’s randomized label cannot be used to infer an analysis population or causal comparison when the relationship between assignment, hearing status, and the listed mask intervention is not explained.

14. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The registry lists serious adverse event counts, other adverse event counts, and deaths separately for the two hearing-status groups. For Normal Hearing, 422 participants were listed as at risk for serious and other adverse events; the recorded affected counts were zero, and deaths were zero. For Hearing Impaired, 13 participants were listed as at risk for each category; the recorded affected counts were zero, and deaths were zero.

These are the counts reported in the registry, not a comparison of event rates or a detailed safety analysis. The record does not list serious adverse event terms, and it reports no affected participants in either group for the displayed categories. The group sizes differ substantially, so a zero count in the smaller group represents observations among fewer participants than a zero count in the larger group. A zero recorded count does not establish that an event is impossible or that all relevant events were captured.

The registry does not provide a detailed adverse-event collection method or further context for interpreting safety events in relation to exposure to the masking intervention. The figures should therefore be read narrowly as the posted counts for these groups and categories, rather than as evidence about risks under unreported conditions or a specific intervention contrast.

15. What the Result Does, and Does Not, Mean

The results show that the posted mean percent-correct score was 69.0 for listeners with normal hearing and 63.0 for listeners with hearing loss. The estimated mean difference, with Hearing Impaired compared with Normal Hearing, was -6.0 percentage points. Its confidence interval ran from -10.79 to -1.214, and the posted unadjusted p value was 0.014. Together, these figures describe a lower mean score in the Hearing Impaired group in the recorded comparison, with uncertainty around the estimated difference.

They do not show that ideal binary masking caused a change in speech intelligibility. Although the registry lists ideal binary mask as the behavioral intervention, the posted primary result compares hearing-status groups and does not provide a mask-versus-comparator estimate. The registry also does not explain what was randomized or how random assignment relates to the hearing-status groups and intervention. The randomized design label alone is not enough to turn this particular group comparison into a causal estimate of masking.

The result is specific to the primary endpoint as described: correctly reported keywords from processed speech phrases, summarized as a mean percent-correct score. The record does not provide separate estimates for different speech types, noise conditions, mask conditions, or participant subgroups. It does not report the detailed task protocol or analysis plan, so the result should not be extended to unreported settings.

The study’s stated goal was proof-of-concept work that could inform a larger evaluation. The posted result is relevant as a group-level observation within that project, but the registry does not establish clinical implications or outcomes beyond the measured task. Its precision is also limited by the unequal group sizes and the relatively small Hearing Impaired group. The estimate and confidence interval should be interpreted together, while keeping the distinction between the observed group association and an intervention effect clear.

16. Why This Trial Matters Statistically

This study raises an important statistical distinction between the question named by an intervention and the comparison actually posted. The registry lists ideal binary mask as the intervention, while the primary result is a mean comparison between listeners with normal hearing and listeners with hearing loss. Without a reported contrast between masking conditions, statistical interpretation must focus on the group comparison rather than assign the observed difference to the intervention.

The result also illustrates why effect estimates should be read alongside uncertainty and group size. The estimated difference is -6.0 percentage points, but the two groups are highly unequal in size, and the Hearing Impaired group has a larger reported standard error. The confidence interval makes the uncertainty around the group contrast visible. Neither the point estimate nor the p value alone provides a complete account of precision or relevance.

Planning calculations offer another statistical lesson. The sample-size illustrations show how planned enrollment changes when a study aims to detect smaller fractions of an observed effect, under stated assumptions. They are useful as conditional planning aids, but they are not a record of the study’s original design choices and do not report observed power.

Finally, sparse reporting affects what can be learned from a completed study. The registry does not describe the analysis population, missing-data procedures, detailed model, or relationship between randomization and the posted groups. These gaps do not erase the reported observations, but they limit the strength and scope of conclusions that can be drawn. Clear alignment among the research question, randomized assignment, outcome contrast, and analysis is essential for interpreting a clinical study statistically.

17. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The main limitation for interpreting this record is the mismatch between the listed intervention and the posted comparison. Ideal binary mask is the named behavioral intervention, yet the arms and primary comparison are organized by hearing status. The registry does not explain how randomization operated, what participants were assigned to, or how that assignment generated the reported group contrast. As a result, the posted estimate cannot be treated as a direct estimate of the masking intervention.

The group sizes are uneven: the Normal Hearing group has 422.0 participants and the Hearing Impaired group has 13.0. The smaller group’s estimate is less precise, as reflected in its reported standard error of 2.2 compared with 1.06 for the larger group. This imbalance makes careful attention to the interval and to the limited information from the smaller group especially important.

The endpoint description identifies a keyword-identification task using processed speech phrases, but the record does not report detailed stimulus, noise, or mask-condition results. It does not show whether the mean summaries combine distinct task conditions or how those conditions were handled analytically. Generalization beyond the posted endpoint and groups is therefore limited.

The registry record does not report the detailed statistical model, analysis population, missing-data approach, or full analysis plan. No secondary outcomes or statistical analyses are posted. These reporting gaps prevent assessment of adjustment choices, multiplicity, exclusions, and robustness. The safety counts are also limited to the displayed categories and do not provide detail about collection procedures or intervention-specific exposure. These limitations concern the information available in the record and should not be mistaken for findings about unreported procedures.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Application of Ideal Binary Masking to Disordered Speech — NCT05244603.
• Registry record last updated 2025-03-26; status last verified 2025-03.
• Results first posted 2025-03-26.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

This completed randomized, unmasked, parallel study, sponsored by Utah State University, examined ideal binary masking in the context of disordered speech and hearing loss. Enrollment was 435, and the registry lists a primary outcome of percent-correct speech intelligibility, measured as the percentage of keywords correctly reported.

The posted primary comparison is between the Normal Hearing group, with 422.0 participants and a mean score of 69.0, and the Hearing Impaired group, with 13.0 participants and a mean score of 63.0. The reported mean difference was -6.0, with a confidence interval from -10.79 to -1.214 and an unadjusted p value of 0.014.

The comparison describes group scores, not a distinct effect estimate for ideal binary mask. The registry does not report the relationship between randomization, intervention exposure, and the posted group contrast, nor does it provide detailed analysis, missing-data, or sample-size design information. The listed serious adverse event, other adverse event, and death counts were zero in both groups.