DIBELS 8th Edition
Composite

Summary

DIBELS 8 composite score is a combination of scores on DIBELS 8 measures and provides an estimate of overall student literacy skill. Scores from all of the relevant subtests for a specific grade are weighted and combined to form a single Composite Score. A confirmatory factor analysis was used to determine the optimal weighting for each of the subtest scores. The Composite Score is scaled so that 400 represents the mean at the middle of year assessment at each grade with 40 as a standard deviation.

Where to Obtain:
University of Oregon, Center on Teaching and Learning
support@dibels.uoregon.edu
5292 University of Oregon Eugene, OR 97403
1-888-497-4290
https://dibels.uoregon.edu
Initial Cost:
Free
Replacement Cost:
Free
Included in Cost:
All materials required for administration are available for free download at https://dibels.uoregon.edu. Printed materials are also available at https://dibels.uoregon.edu/market for a cost of $53 to $91 for a classroom set of benchmark screening materials. The DIBELS Data System (DDS) is not required, but is available for online data entry, management and reporting for a cost of $1.00 per student per year. A multi-year discount is currently available. The DDS is free-of-charge to schools in Oregon. For the most current pricing information see: https://dibels.uoregon.edu/help/pricing. Additional costs are associated with printing, and computer and internet access if also using the DIBELS Data System. Starting in the 2019-20 school year, tablet-based administration will be available from Amplify (https://www.amplify.com).
DIBELS 8th Edition approved assessment accommodations involve minor changes to assessment procedures that are unlikely to change the meaning of the results and have been approved either by DIBELS developers or assessment professionals. They should be used only when: • An accurate score is unlikely to be obtained without the accommodation; and/or • Specified in a student’s 504 plan or Individualized Education Plan (IEP). The accommodations approved for DIBELS 8th Edition are: quiet setting for testing; breaks in between measures; assistive technology (e.g., hearing aids, assistive listening devices, glasses); enlarged student materials; colored overlays, filters, or lighting adjustments; and marker or ruler for tracking.
Training Requirements:
4-8 hours of training
Qualified Administrators:
Paraprofessional
Access to Technical Support:
Technical support is available from the DIBELS Data System at the University of Oregon, https://dibels.uoregon.edu (phone: 1-888-497-4290, email: support@dibels.uoregon.edu, hours of operation: 6:00am to 5:30pm Pacific Time, Monday through Friday).
Assessment Format:
  • Direct observation
  • Performance measure
  • One-to-one
Scoring Time:
  • Scoring is automatic OR
  • 5 minutes per student
Scores Generated:
  • Percentile score
  • Developmental benchmarks
  • Developmental cut points
  • Composite scores
  • Subscale/subtest scores
Administration Time:
  • 6 minutes per student
Scoring Method:
  • Manually (by hand)
  • Automatically (computer-scored)
Technology Requirements:
Accommodations:
DIBELS 8th Edition approved assessment accommodations involve minor changes to assessment procedures that are unlikely to change the meaning of the results and have been approved either by DIBELS developers or assessment professionals. They should be used only when: • An accurate score is unlikely to be obtained without the accommodation; and/or • Specified in a student’s 504 plan or Individualized Education Plan (IEP). The accommodations approved for DIBELS 8th Edition are: quiet setting for testing; breaks in between measures; assistive technology (e.g., hearing aids, assistive listening devices, glasses); enlarged student materials; colored overlays, filters, or lighting adjustments; and marker or ruler for tracking.

Descriptive Information

Please provide a description of your tool:
DIBELS 8 composite score is a combination of scores on DIBELS 8 measures and provides an estimate of overall student literacy skill. Scores from all of the relevant subtests for a specific grade are weighted and combined to form a single Composite Score. A confirmatory factor analysis was used to determine the optimal weighting for each of the subtest scores. The Composite Score is scaled so that 400 represents the mean at the middle of year assessment at each grade with 40 as a standard deviation.
The tool is intended for use with the following grade(s).
not selected Preschool / Pre - kindergarten
selected Kindergarten
selected First grade
selected Second grade
selected Third grade
selected Fourth grade
selected Fifth grade
selected Sixth grade
selected Seventh grade
selected Eighth grade
not selected Ninth grade
not selected Tenth grade
not selected Eleventh grade
not selected Twelfth grade

The tool is intended for use with the following age(s).
not selected 0-4 years old
not selected 5 years old
not selected 6 years old
not selected 7 years old
not selected 8 years old
not selected 9 years old
not selected 10 years old
not selected 11 years old
not selected 12 years old
not selected 13 years old
not selected 14 years old
not selected 15 years old
not selected 16 years old
not selected 17 years old
not selected 18 years old

The tool is intended for use with the following student populations.
not selected Students in general education
not selected Students with disabilities
not selected English language learners

ACADEMIC ONLY: What skills does the tool screen?

Reading
Phonological processing:
not selected RAN
not selected Memory
selected Awareness
selected Letter sound correspondence
selected Phonics
not selected Structural analysis

Word ID
selected Accuracy
selected Speed

Nonword
selected Accuracy
selected Speed

Spelling
not selected Accuracy
not selected Speed

Passage
selected Accuracy
selected Speed

Reading comprehension:
not selected Multiple choice questions
not selected Cloze
not selected Constructed Response
not selected Retell
selected Maze
not selected Sentence verification
not selected Other (please describe):


Listening comprehension:
not selected Multiple choice questions
not selected Cloze
not selected Constructed Response
not selected Retell
not selected Maze
not selected Sentence verification
not selected Vocabulary
not selected Expressive
not selected Receptive

Mathematics
Global Indicator of Math Competence
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Early Numeracy
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Mathematics Concepts
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Mathematics Computation
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Mathematic Application
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Fractions/Decimals
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Algebra
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

Geometry
not selected Accuracy
not selected Speed
not selected Multiple Choice
not selected Constructed Response

not selected Other (please describe):

Please describe specific domain, skills or subtests:
BEHAVIOR ONLY: Which category of behaviors does your tool target?


BEHAVIOR ONLY: Please identify which broad domain(s)/construct(s) are measured by your tool and define each sub-domain or sub-construct.

Acquisition and Cost Information

Where to obtain:
Email Address
support@dibels.uoregon.edu
Address
5292 University of Oregon Eugene, OR 97403
Phone Number
1-888-497-4290
Website
https://dibels.uoregon.edu
Initial cost for implementing program:
Cost
$0.00
Unit of cost
Replacement cost per unit for subsequent use:
Cost
$0.00
Unit of cost
Duration of license
Additional cost information:
Describe basic pricing plan and structure of the tool. Provide information on what is included in the published tool, as well as what is not included but required for implementation.
All materials required for administration are available for free download at https://dibels.uoregon.edu. Printed materials are also available at https://dibels.uoregon.edu/market for a cost of $53 to $91 for a classroom set of benchmark screening materials. The DIBELS Data System (DDS) is not required, but is available for online data entry, management and reporting for a cost of $1.00 per student per year. A multi-year discount is currently available. The DDS is free-of-charge to schools in Oregon. For the most current pricing information see: https://dibels.uoregon.edu/help/pricing. Additional costs are associated with printing, and computer and internet access if also using the DIBELS Data System. Starting in the 2019-20 school year, tablet-based administration will be available from Amplify (https://www.amplify.com).
Provide information about special accommodations for students with disabilities.
DIBELS 8th Edition approved assessment accommodations involve minor changes to assessment procedures that are unlikely to change the meaning of the results and have been approved either by DIBELS developers or assessment professionals. They should be used only when: • An accurate score is unlikely to be obtained without the accommodation; and/or • Specified in a student’s 504 plan or Individualized Education Plan (IEP). The accommodations approved for DIBELS 8th Edition are: quiet setting for testing; breaks in between measures; assistive technology (e.g., hearing aids, assistive listening devices, glasses); enlarged student materials; colored overlays, filters, or lighting adjustments; and marker or ruler for tracking.

Administration

BEHAVIOR ONLY: What type of administrator is your tool designed for?
not selected General education teacher
not selected Special education teacher
not selected Parent
not selected Child
not selected External observer
not selected Other
If other, please specify:

What is the administration setting?
selected Direct observation
not selected Rating scale
not selected Checklist
selected Performance measure
not selected Questionnaire
not selected Direct: Computerized
selected One-to-one
not selected Other
If other, please specify:

Does the tool require technology?
No

If yes, what technology is required to implement your tool? (Select all that apply)
not selected Computer or tablet
not selected Internet connection
not selected Other technology (please specify)

If your program requires additional technology not listed above, please describe the required technology and the extent to which it is combined with teacher small-group instruction/intervention:
Administering the measure does not require technology, but if users choose to use the DIBELS Data System for management and reporting of data, an internet connected computer is required. Additionally, if schools choose to administer the DIBELS 8th Edition measures using a tablet, they should contact Amplify for technology requirements.

What is the administration context?
selected Individual
selected Small group   If small group, n=
selected Large group   If large group, n=
not selected Computer-administered
not selected Other
If other, please specify:

What is the administration time?
Time in minutes
6
per (student/group/other unit)
student

Additional scoring time:
Time in minutes
5
per (student/group/other unit)
student

ACADEMIC ONLY: What are the discontinue rules?
not selected No discontinue rules provided
not selected Basals
not selected Ceilings
selected Other
If other, please specify:
Discontinue rules are specified for each subtest


Are norms available?
Yes
Are benchmarks available?
Yes
If yes, how many benchmarks per year?
3
If yes, for which months are benchmarks available?
Benchmarks are available for the beginning, middle and end of the school year. Beginning months are typically September, October and November; middle months are December, January, and February; and end months are typically March, April, May and June. Regardless of when the benchmark occurs, we recommend that all students are tested within a one-month window.
BEHAVIOR ONLY: Can students be rated concurrently by one administrator?
If yes, how many students can be rated concurrently?

Training & Scoring

Training

Is training for the administrator required?
Yes
Describe the time required for administrator training, if applicable:
4-8 hours of training
Please describe the minimum qualifications an administrator must possess.
Paraprofessional
not selected No minimum qualifications
Are training manuals and materials available?
Yes
Are training manuals/materials field-tested?
Yes
Are training manuals/materials included in cost of tools?
No
If No, please describe training costs:
Information about online training is available on the DIBELS Data System (https://dibels.uoregon.edu/training). Online training is free-of-charge for ‘early adopters’ (i.e., schools or districts that sign up for the next school year by a specified date in spring.) For people not associated with the ‘early adopter’ program the charge is $40 to $79 per person, depending on the number of people purchasing the training, and whether an individual is associated with a DDS account.
Can users obtain ongoing professional and technical support?
Yes
If Yes, please describe how users can obtain support:
Technical support is available from the DIBELS Data System at the University of Oregon, https://dibels.uoregon.edu (phone: 1-888-497-4290, email: support@dibels.uoregon.edu, hours of operation: 6:00am to 5:30pm Pacific Time, Monday through Friday).

Scoring

How are scores calculated?
selected Manually (by hand)
selected Automatically (computer-scored)
not selected Other
If other, please specify:

Do you provide basis for calculating performance level scores?
Yes
What is the basis for calculating performance level and percentile scores?
not selected Age norms
selected Grade norms
not selected Classwide norms
not selected Schoolwide norms
not selected Stanines
not selected Normal curve equivalents

What types of performance level scores are available?
not selected Raw score
not selected Standard score
selected Percentile score
not selected Grade equivalents
not selected IRT-based score
not selected Age equivalents
not selected Stanines
not selected Normal curve equivalents
selected Developmental benchmarks
selected Developmental cut points
not selected Equated
not selected Probability
not selected Lexile score
not selected Error analysis
selected Composite scores
selected Subscale/subtest scores
not selected Other
If other, please specify:

Does your tool include decision rules?
Yes
If yes, please describe.
Two cut points are available for DIBELS 8th Edition Composite Scores to help educators determine where to allocate resources and how much intervention students may need. One cut point indicates that students are likely at risk for difficulty in learning to read. The other is a benchmark cut point that indicates if students are likely to be on track. Students between the two cut points are considered to be somewhere between “at-risk” and “on track”.
Can you provide evidence in support of multiple decision rules?
Yes
If yes, please describe.
This application addresses the “at-risk” cut point. Information about benchmark cut points is available on the DIBELS Data System website https://dibels.uoregon.edu.
Please describe the scoring structure. Provide relevant details such as the scoring format, the number of items overall, the number of items per subscale, what the cluster/composite score comprises, and how raw scores are calculated.
Describe the tool’s approach to screening, samples (if applicable), and/or test format, including steps taken to ensure that it is appropriate for use with culturally and linguistically diverse populations and students with disabilities.
The DIBELS 8 Composite Score represents a weighted combination of scores on all DIBELS 8 measures that are required for a particular grade and provides an estimate of overall student literacy skill. The Composite Score was developed based on data from a nationally representative sample of students in kindergarten through grade 8, using a confirmatory factor analysis (CFA) approach in which multiple theoretical one-factor reading models were constructed based on theories on literacy development and literacy assessment. Those models were then tested empirically to identify the model for each grade that best fit the data. The reading factor models were built starting with a base model for each grade, where all DIBELS 8 measures were loaded on the common reading factor. Then, the base model was extended by modeling different types of covariances. In the reading factor models for grades K–3, modeling ORF(WRC) – ORF (ACC) covariance and NWF (CLS) – NWF (WRC) covariance takes into account the residuals that multiple scores are derived from the same subtest. Modeling ORF – WRF covariance takes into account residuals associated with measures that share the task of reading real words, while the WRF – NWF(WRC) covariance accounts for the residuals associated with measuring blending words. Modeling ORF (WRC) – Maze covariance takes into account the residuals associated with measuring reading comprehension. The final model for each grade level was determined by comparing model fits. Fit of the models was evaluated using the comparative fit index (CFI; Bentler, 1990; acceptable fit ≥ .95), root mean square error of approximation (RMSEA; Browne & Cudeck, 1993; acceptable fit ≤ .06), the standardized root mean square residual (RMSR; Hu & Bentler, 1998; acceptable fit ≤ .10), Akaike information criterion (AIC; Burnham & Anderson; the lower the better), and Bayesian information criterion (BIC; Burnham & Anderson; the lower the better). Maximum likelihood was used to estimate the model. The resulting best-fitting reading factor model for grades K–3 included the available DIBELS 8 measures for each grade level and the NWF (CLS) – NWF (WRC) covariance. The best-fitting reading model for grades 4–8 included all the available DIBELS 8 measures but no covariances. Unstandardized factor loadings in the final reading models were all statistically significant. We then used the “regression method” (Thurston, 1935) to combine scores on DIBELS 8 measures and compute the composite scores. The DIBELS 8 Composite Score is thus calculated as a sum of the weighted standardized observed values of each of the measures in the estimated latent reading factor with a mean of zero and standard deviation of 1. The least square regression method used is a multivariate procedure that accounts for the correlations among the observed variables as well as the correlations between the factors and between the factors and observed variables (DiStefano, Zhu, & Mîndrilă, 2009).

Technical Standards

Classification Accuracy & Cross-Validation Summary

Grade Kindergarten
Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Grade 6
Grade 7
Grade 8
Classification Accuracy for Criterion 1 Fall Partially convincing evidence Partially convincing evidence Unconvincing evidence Partially convincing evidence Convincing evidence Partially convincing evidence Unconvincing evidence Convincing evidence Unconvincing evidence
Classification Accuracy for Criterion 1 Winter Convincing evidence Partially convincing evidence Convincing evidence Partially convincing evidence Convincing evidence Convincing evidence Unconvincing evidence Convincing evidence Unconvincing evidence
Classification Accuracy for Criterion 1 Spring Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable
Classification Accuracy for Criterion 2 Fall Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable
Classification Accuracy for Criterion 2 Winter Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable
Classification Accuracy for Criterion 2 Spring Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable Data unavailable
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available

Classification Accuracy - Criterion 1 Fall

Evidence Kindergarten Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8
Criterion measure DIBELS Next Composite Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score
Cut Points - Percentile rank on criterion measure 20 20 20 20 20 20 20 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 298 322 315 313 308 312 321 313 344
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC) 0.87 0.86 0.90 0.72 0.89 0.78 0.84 0.93 0.89
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.82 0.79 0.84 0.58 0.83 0.66 0.69 0.82 0.79
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.92 0.93 0.96 0.87 0.94 0.90 0.99 1.00 0.98
Statistics Kindergarten Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Kindergarten Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8
Date Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019
Sample Size
Geographic Representation East North Central (OH)
Middle Atlantic (PA)
West North Central (MO)
West South Central (AR, TX)
East North Central (OH)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (GA)
West North Central (MO)
East North Central (OH)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (FL, GA)
West North Central (MO)
East North Central (OH)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (FL, GA)
West North Central (MO)
East North Central (OH)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (FL, GA)
West North Central (MO)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (GA)
West North Central (MO)
Mountain (AZ)
Pacific (WA)
South Atlantic (FL, GA)
West North Central (MO)
Mountain (AZ)
Pacific (WA)
South Atlantic (FL, GA)
West North Central (MO)
Mountain (AZ)
South Atlantic (GA)
West North Central (MO)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Classification Accuracy - Criterion 1 Winter

Evidence Kindergarten Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8
Criterion measure DIBELS Next Composite Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score Iowa Assessment Total Reading Score
Cut Points - Percentile rank on criterion measure 20 20 20 20 20 20 20 20 20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure 364 374 372 376 378 378 378 373 384
Classification Data - True Positive (a)
Classification Data - False Positive (b)
Classification Data - False Negative (c)
Classification Data - True Negative (d)
Area Under the Curve (AUC) 0.92 0.85 0.93 0.82 0.92 0.88 0.89 0.92 0.86
AUC Estimate’s 95% Confidence Interval: Lower Bound 0.88 0.78 0.89 0.72 0.87 0.81 0.79 0.85 0.75
AUC Estimate’s 95% Confidence Interval: Upper Bound 0.95 0.91 0.97 0.91 0.98 0.95 0.99 0.99 0.96
Statistics Kindergarten Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power
Sample Kindergarten Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8
Date Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019 Spring 2019
Sample Size
Geographic Representation East North Central (OH)
Middle Atlantic (PA)
West North Central (MO)
West South Central (AR, TX)
East North Central (OH)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (GA)
West North Central (MO)
East North Central (OH)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (FL, GA)
West North Central (MO)
East North Central (OH)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (FL, GA)
West North Central (MO)
East North Central (OH)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (FL, GA)
West North Central (MO)
Mountain (AZ)
Pacific (OR, WA)
South Atlantic (GA)
West North Central (MO)
Mountain (AZ)
Pacific (WA)
South Atlantic (FL, GA)
West North Central (MO)
Mountain (AZ)
Pacific (WA)
South Atlantic (FL, GA)
West North Central (MO)
Mountain (AZ)
South Atlantic (GA)
West North Central (MO)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Reliability

Grade Kindergarten
Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Grade 6
Grade 7
Grade 8
Rating Unconvincing evidence Unconvincing evidence Unconvincing evidence Unconvincing evidence Unconvincing evidence Unconvincing evidence Unconvincing evidence Unconvincing evidence Unconvincing evidence
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available
*Offer a justification for each type of reliability reported, given the type and purpose of the tool.
To assess the reliability of DIBELS 8th Edition, we evaluated multiple forms of reliability, including test-retest reliability, concurrent alternate form reliability, and delayed alternate form reliability. We include delayed alternate form reliability as a supplementary source of reliability evidence by reporting correlations between two or more alternate form of the same test administered at different time points (e.g., different seasons). Test-retest reliability: Test-retest reliability was evaluated by administering the same test (i.e., set of items) to the same individuals two times and correlating scores from the two test administrations. We included test-retest reliability in cases where the only source of alternate form reliability was delayed alternate form. In those instances, test-retest reliability provides some measure of reliability without the confound of the (expected) student growth between administrations. Alternate-form reliability: Alternate-form reliability indicates the extent to which test results generalize to different item samples. To assess alternate-form reliability, students were administered multiple forms of each subtest, and scores from these two forms were correlated. Concurrent alternate-form reliability of a single (i.e., benchmark) form was estimated by the correlation between the score on that form and the score on an alternate (i.e., progress monitoring) form. Delayed alternate form reliability was estimated by correlating scores measured at different benchmark administrations across year—beginning-, middle-, and end of year. The use of alternate form reliability is justified because it uses different but equivalent forms, thereby preventing practice effects inherent in test-retest reliability where the same form is administered twice. In addition, it is important to establish that different forms are equivalent given the use of different forms for progress-monitoring across the year.
*Describe the sample(s), including size and characteristics, for each reliability analysis conducted.
Twenty-one schools administered DIBELS 8th Edition to 5,259 students in grades K - 8. The schools were located in the Pacific, East North Central, West North Central, Mountain, and South Atlantic census divisions. Schools represent towns, large cities, suburbs and rural areas. The sample of students was 50.6% male and 48.9% female; 1.5% American Indian or Alaskan Native; 2.5% Asian, 17.2% Black, 20.9% Hispanic, 4.1% two or more races, 0.4% Native Hawaiian/Pacific Islander, and 53.0% White. 13.9% of students had disabilities, 59.6% were eligible for free or reduced lunch, and 7.3% were English learners.
*Describe the analysis procedures for each reported type of reliability.
Alternate form reliability: Students were administered multiple forms of each subtest, and scores from these two forms were correlated. Delayed alternate form reliability was estimated by correlating scores measured at different benchmark administrations across year—beginning-, middle-, and end of year.

*In the table(s) below, report the results of the reliability analyses described above (e.g., internal consistency or inter-rater reliability coefficients).

Type of Subgroup Informant Age / Grade Test or Criterion n Median Coefficient 95% Confidence Interval
Lower Bound
95% Confidence Interval
Upper Bound
Results from other forms of reliability analysis not compatible with above table format:
Manual cites other published reliability studies:
Provide citations for additional published studies.
Do you have reliability data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?

If yes, fill in data for each subgroup with disaggregated reliability data.

Type of Subgroup Informant Age / Grade Test or Criterion n Median Coefficient 95% Confidence Interval
Lower Bound
95% Confidence Interval
Upper Bound
Results from other forms of reliability analysis not compatible with above table format:
Manual cites other published reliability studies:
Provide citations for additional published studies.

Validity

Grade Kindergarten
Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Grade 6
Grade 7
Grade 8
Rating Partially convincing evidence Partially convincing evidence Partially convincing evidence Partially convincing evidence Partially convincing evidence Partially convincing evidence Unconvincing evidence Partially convincing evidence Unconvincing evidence
Legend
Full BubbleConvincing evidence
Half BubblePartially convincing evidence
Empty BubbleUnconvincing evidence
Null BubbleData unavailable
dDisaggregated data available
*Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.
The DIBELS 8th Edition Composite Score in kindergarten through grade 8 was validated against multiple criterion measures drawn from DIBELS Next and the Iowa Assessment of Reading. DIBELS Next criterion measures were DIBELS Next Nonsense Word Fluency, Oral Reading Fluency, and Composite Score and provided both concurrent and predictive validity evidence. The DIBELS Next Composite score is comprised of the individual DIBELS Next subtests administered in a given grade and time of year. The DIBELS Next measure scores are appropriate because they assess reading and were developed independently and administered separately from DIBELS 8th Edition. The Iowa Assessment of Reading provided two criterion measures: Total Reading score and Word Analysis score. The Iowa Assessment is a commonly accepted measure of reading achievement. It is a published, group-administered, multiple-choice, norm-referenced test of reading. The Word Analysis measure focuses on decoding skills, while the Total Reading measure assesses reading achievement more broadly. Iowa assessments are completely independent of DIBELS 8th Edition measures.
*Describe the sample(s), including size and characteristics, for each validity analysis conducted.
Twenty-one schools administered DIBELS 8th Edition to 5,259 students in grades K - 8. The schools were located in the Pacific, East North Central, West North Central, Mountain, and South Atlantic census divisions. Schools represent towns, large cities, suburbs and rural areas. The sample of students was 50.6% male and 48.9% female; 1.5% American Indian or Alaskan Native; 2.5% Asian, 17.2% Black, 20.9% Hispanic, 4.1% two or more races, 0.4% Native Hawaiian/Pacific Islander, and 53.0% White. 13.9% of students had disabilities, 59.6% were eligible for free or reduced lunch, and 7.3% were English learners.
*Describe the analysis procedures for each reported type of validity.
Concurrent validity: Concurrent validity was evaluated by examining the strength of correlation between the screening measure and the criterion measures administered at approximately the same time of the year. Predictive validity: Predictive validity was evaluated by examining the strength of correlation between the screening measure and the student future performance on the criterion measures.

*In the table below, report the results of the validity analyses described above (e.g., concurrent or predictive validity, evidence based on response processes, evidence based on internal structure, evidence based on relations to other variables, and/or evidence based on consequences of testing), and the criterion measures.

Type of Subgroup Informant Age / Grade Test or Criterion n Median Coefficient 95% Confidence Interval
Lower Bound
95% Confidence Interval
Upper Bound
Results from other forms of validity analysis not compatible with above table format:
Manual cites other published reliability studies:
Provide citations for additional published studies.
Describe the degree to which the provided data support the validity of the tool.
Overall, the validity of the DIBELS 8th Edition composite Score is well supported by a range of concurrent and predictive validity correlations across multiple criterion measures. Lower correlations are indicative of greater lengths of time between administrations (and thus, more opportunity for student growth) and/or weaker alignment between constructs being measured.
Do you have validity data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?

If yes, fill in data for each subgroup with disaggregated validity data.

Type of Subgroup Informant Age / Grade Test or Criterion n Median Coefficient 95% Confidence Interval
Lower Bound
95% Confidence Interval
Upper Bound
Results from other forms of validity analysis not compatible with above table format:
Manual cites other published reliability studies:
Provide citations for additional published studies.

Bias Analysis

Grade Kindergarten
Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Grade 6
Grade 7
Grade 8
Rating No No No No No No No No No
Have you conducted additional analyses related to the extent to which your tool is or is not biased against subgroups (e.g., race/ethnicity, gender, socioeconomic status, students with disabilities, English language learners)? Examples might include Differential Item Functioning (DIF) or invariance testing in multiple-group confirmatory factor models.
No
If yes,
a. Describe the method used to determine the presence or absence of bias:
b. Describe the subgroups for which bias analyses were conducted:
c. Describe the results of the bias analyses conducted, including data and interpretative statements. Include magnitude of effect (if available) if bias has been identified.

Data Collection Practices

Most tools and programs evaluated by the NCII are branded products which have been submitted by the companies, organizations, or individuals that disseminate these products. These entities supply the textual information shown above, but not the ratings accompanying the text. NCII administrators and members of our Technical Review Committees have reviewed the content on this page, but NCII cannot guarantee that this information is free from error or reflective of recent changes to the product. Tools and programs have the opportunity to be updated annually or upon request.