DIBELS 6th Edition
Letter Naming Fluency

Descriptive Information

Please provide a description of your tool:

DIBELS 6th Edition Letter Naming Fluency (LNF) is a standardized, individually administered measure of a student’s accuracy and fluency with naming a series of upper- and lower-case letters of the alphabet. The measure is designed as an indicator of later reading risk for students in kindergarten and first grade. The measure is timed for one-minute. Letters omitted, substituted, and hesitations of more than three seconds are scored as errors. Letters self-corrected within three seconds are scored as accurate. The number of correct letters named in 1-minute is the letter naming fluency rate. Cut points for intensive intervention are addressed in this application. Benchmark cut points, as well as cut points for intensive intervention, are available at https://dibels.uoregon.edu/docs/marketplace/dibels/DIBELS-6Ed-Goals.pdf

The tool is intended for use with the following grade(s).

Preschool / Pre - kindergarten
Kindergarten
First grade
Second grade
Third grade
Fourth grade
Fifth grade
Sixth grade
Seventh grade
Eighth grade
Ninth grade
Tenth grade
Eleventh grade
Twelfth grade

The tool is intended for use with the following age(s).

0-4 years old
5 years old
6 years old
7 years old
8 years old
9 years old
10 years old
11 years old
12 years old
13 years old
14 years old
15 years old
16 years old
17 years old
18 years old

The tool is intended for use with the following student populations.

Students in general education
Students with disabilities
English language learners

ACADEMIC ONLY: What skills does the tool screen?

Reading

Phonological processing:

RAN
Memory
Awareness
Letter sound correspondence
Phonics
Structural analysis

Word ID

Accuracy
Speed

Nonword

Accuracy
Speed

Spelling

Accuracy
Speed

Passage

Accuracy
Speed

Reading comprehension:

Multiple choice questions
Cloze
Constructed Response
Retell
Maze
Sentence verification
Other (please describe):

Listening comprehension:

Multiple choice questions
Cloze
Constructed Response
Retell
Maze
Sentence verification
Vocabulary
Expressive
Receptive

Mathematics

Global Indicator of Math Competence

Accuracy
Speed
Multiple Choice
Constructed Response

Early Numeracy

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematics Concepts

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematics Computation

Accuracy
Speed
Multiple Choice
Constructed Response

Mathematic Application

Accuracy
Speed
Multiple Choice
Constructed Response

Fractions/Decimals

Accuracy
Speed
Multiple Choice
Constructed Response

Algebra

Accuracy
Speed
Multiple Choice
Constructed Response

Geometry

Accuracy
Speed
Multiple Choice
Constructed Response

Other (please describe):

Please describe specific domain, skills or subtests:

BEHAVIOR ONLY: Which category of behaviors does your tool target?

Internalizing
Externalizing
Internalizing and Externalizing

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

student

Replacement cost per unit for subsequent use:

Cost

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. 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. Included with the DDS service is optional tablet based administration through the HiFi Reading app available for free download at the Apple app store. Training is required for assessors and is available through online DDS training modules. The cost of the training ranges from $40- $79 per person. Additional costs include the cost of printing and the cost of a computer (required) and tablets (optional).

Provide information about special accommodations for students with disabilities.

The DIBELS directions are designed to be used unmodified with all students. They have been validated with tens of thousands of students to work the way they do. In a very small number of cases though, a small number of accommodations are approved. They are used only in situations where they are necessary to obtain an accurate score for a student. When approved accommodations are used, the examiner should mark an “A” on the front cover of the testing booklet. Scores with accommodations can be used as any another of DIBELS scores. Approved accommodations should only be used with students who have a documented need for such supports, not to improve performance for multiple students. DIBELS 6th Edition approved accommodations for LNF are: • Enlarged student materials • Colored overlays, filters or lighting adjustments • Assistive technology (e.g., hearing aids, assistive listening devices) • Marker or ruler for tracking

Administration

BEHAVIOR ONLY: What type of administrator is your tool designed for?

General education teacher
Special education teacher
Parent
Child
External observer
Other

If other, please specify:

What is the administration setting?

Direct observation
Rating scale
Checklist
Performance measure
Questionnaire
Direct: Computerized
One-to-one
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)

Computer or tablet
Internet connection
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:

What is the administration context?

Individual
Small group   If small group, n=
Large group   If large group, n=
Computer-administered
Other

If other, please specify:

What is the administration time?

Time in minutes

2

per (student/group/other unit)

student

Additional scoring time:

Time in minutes

1

per (student/group/other unit)

student

ACADEMIC ONLY: What are the discontinue rules?

No discontinue rules provided
Basals
Ceilings
Other

If other, please specify:

No letters correct in the first row

Are norms available?

Yes

Are benchmarks available?

Yes

If yes, how many benchmarks per year?

Three benchmarks for kindergarten (beginning, middle and end of year) and one for first grade (beginning of year). Beginning- and middle-of-year benchmarks are included for review in this submission.

If yes, for which months are benchmarks available?

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. If DIBELS LNF is administered outside of that one month time frame, it should not be entered as the benchmark score for the student.

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:

1-4 hours of training

Please describe the minimum qualifications an administrator must possess.

Paraprofessional

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:

Online training for administration and scoring of DIBELS 6th edition is available at https://dibels.uoregon.edu/training/. The cost of the training ranges from $40- $79 per person and includes all DIBELS 6th Edition subtests. Cost depends on whether a group discount is applied, and whether the trainee is a DIBELS Data System customer.

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?

Manually (by hand)
Automatically (computer-scored)
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?

Age norms
Grade norms
Classwide norms
Schoolwide norms
Stanines
Normal curve equivalents

What types of performance level scores are available?

Raw score
Standard score
Percentile score
Grade equivalents
IRT-based score
Age equivalents
Stanines
Normal curve equivalents
Developmental benchmarks
Developmental cut points
Equated
Probability
Lexile score
Error analysis
Composite scores
Subscale/subtest scores
Other

If other, please specify:

Does your tool include decision rules?

Yes

If yes, please describe.

Grade-based, empirically determined cut points for risk and benchmark goals, based on ROC analyses predicting performance at the 20th and 40th percentile on the SAT-10 Total Reading.

Can you provide evidence in support of multiple decision rules?

Yes

If yes, please describe.

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.

A composite score is not available.

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.

DIBELS LNF is a standardized, individually administered measure of a student’s accuracy and fluency with naming a series of upper- and lower-case letters of the alphabet. The measure is designed as an indicator of later reading risk for students in kindergarten and first grade. The measure is timed for one-minute. Letters omitted, substituted, and hesitations of more than three seconds are scored as errors. Letters self-corrected within three seconds are scored as accurate. The number of correct letters named in 1-minute is the letter naming fluency rate. There are specific scoring rules regarding articulation and dialect to mitigate linguistic bias. Students are not penalized for differences in speech production that are the result of dialect, first-language, or articulation.

Classification Accuracy & Cross-Validation Summary

Grade	Kindergarten	Grade 1
Classification Accuracy Fall
Classification Accuracy Winter
Classification Accuracy Spring

Stanford Achievement Test: 10th Edition (SAT-10)

Classification Accuracy

Select time of year

Fall

Winter

Spring

Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.

The Stanford Achievement Test – 10th Edition (SAT-10; Harcourt Educational Measurement, 2002) was administered to students in Grades 1 and 2. The SAT-10 is a group-administered, norm-referenced test of overall reading proficiency. The SAT-10 is not timed, although guidelines with flexible time recommendations are given. In first grade, all four recommended subtests were administered: Word Study Skills, Word Reading, Sentence Reading, and Reading Comprehension. This battery takes about 155 minutes to complete. In Grade 2, three subtests were administered: Word Study Skills, Reading Vocabulary, and Reading Comprehension. Kuder-Richardson reliability coefficients for total reading scores were .97 at Grade 1 and .95 at Grade 2. Correlations between the total reading score and the Otis-Lennon School Ability Test ranged from .61 to .75. The normative sample is representative of the U.S. student population.

Do the classification accuracy analyses examine concurrent and/or predictive classification?

Concurrent
Predictive

Describe when screening and criterion measures were administered and provide a justification for why the method(s) you chose (concurrent and/or predictive) is/are appropriate for your tool.

Describe how the classification analyses were performed and cut-points determined. Describe how the cut points align with students at-risk. Please indicate which groups were contrasted in your analyses (e.g., low risk students versus high risk students, low risk students versus moderate risk students).

We used a two-stage process for determining cut-points for intensive need. First, we plotted Receiver Operating Characteristic (ROC) curves at each time point and grade and the associated end-of-year criterion measure and determined the area under the curve (A). Prior to conducting our analyses, we decided to calculate cut points only for those measures and time points where the AUC met or exceeded .75. An AUC of less than .75 suggests that the measure may not represent accuracy beyond teacher judgment, and we believe that providing cut-points for measures with an AUC value less than .75 would imply greater confidence in the measures than is warranted. Second, we conducted a diagnostic analysis of each measure at each time point (i.e., season. For each analysis, we examined two statistics: sensitivity and specificity. We chose to focus on sensitivity and specificity (rather than PPV and NPV) because they remain stable indicators regardless of the prevalence of reading difficulties in the population (Pepe, 2003). Further, we emphasized sensitivity in our analyses because of its practical application in a prevention model in education. Specifically, we want to be confident that students receive the instructional support they require as early as possible. All cut-points were determined using an optimal decision threshold associated with sensitivity at or above .80. This criterion roughly corresponds to the statement that, we will miss an opportunity to provide additional support to only 20% of students who are likely to score below the 20th percentile on the SAT10.

Were the children in the study/studies involved in an intervention in addition to typical classroom instruction between the screening measure and outcome assessment?

Yes

If yes, please describe the intervention, what children received the intervention, and how they were chosen.

All students were part of the Oregon Reading First study. Each participating school provided at least 90 minutes of daily, scientifically based reading instruction for all kindergarten through third-grade students with a minimum of 30 minutes of daily small-group, teacher-directed reading instruction.

Cross-Validation

Has a cross-validation study been conducted?

No

If yes,

Select time of year.

Fall

Winter

Spring

Describe the criterion (outcome) measure(s) including the degree to which it/they is/are independent from the screening measure.

Do the cross-validation analyses examine concurrent and/or predictive classification?

Concurrent
Predictive

Describe when screening and criterion measures were administered and provide a justification for why the method(s) you chose (concurrent and/or predictive) is/are appropriate for your tool.

Describe how the cross-validation analyses were performed and cut-points determined. Describe how the cut points align with students at-risk. Please indicate which groups were contrasted in your analyses (e.g., low risk students versus high risk students, low risk students versus moderate risk students).

Were the children in the study/studies involved in an intervention in addition to typical classroom instruction between the screening measure and outcome assessment?

If yes, please describe the intervention, what children received the intervention, and how they were chosen.

---

Classification Accuracy - Fall

Evidence	Kindergarten	Grade 1
Criterion measure	Stanford Achievement Test: 10th Edition (SAT-10)	Stanford Achievement Test: 10th Edition (SAT-10)
Cut Points - Percentile rank on criterion measure	20	20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	6 correct letters	33 correct letters
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)	0.77	0.82
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.76	0.81
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.78	0.83

Statistics	Kindergarten	Grade 1
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Kindergarten	Grade 1
Date	2003-06
Sample Size
Geographic Representation	Pacific (OR)	Pacific (OR)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian/Pacific Islander
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Classification Accuracy - Winter

Evidence	Kindergarten
Criterion measure	Stanford Achievement Test: 10th Edition (SAT-10)
Cut Points - Percentile rank on criterion measure	20
Cut Points - Performance score on criterion measure
Cut Points - Corresponding performance score (numeric) on screener measure	27 correct letters
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)	0.84
AUC Estimate’s 95% Confidence Interval: Lower Bound	0.83
AUC Estimate’s 95% Confidence Interval: Upper Bound	0.85

Statistics	Kindergarten
Base Rate
Overall Classification Rate
Sensitivity
Specificity
False Positive Rate
False Negative Rate
Positive Predictive Power
Negative Predictive Power

Sample	Kindergarten
Date	2003-06
Sample Size
Geographic Representation	Pacific (OR)
Male
Female
Other
Gender Unknown
White, Non-Hispanic
Black, Non-Hispanic
Hispanic
Asian/Pacific Islander
American Indian/Alaska Native
Other
Race / Ethnicity Unknown
Low SES
IEP or diagnosed disability
English Language Learner

Reliability

Grade	Kindergarten	Grade 1
Rating

*Offer a justification for each type of reliability reported, given the type and purpose of the tool.

We evaluated alternate form reliability and test-retest reliability to assess the reliability of DIBELS 6th Edition LNF subtest. Alternate form reliability: Alternate-form reliability indicates the extent to which test results generalize to different item samples. Students are tested with two or more different (i.e., alternate) but equivalent forms of the test within some relatively short interval of time, and scores from these forms are correlated. 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 need to use different forms for progress-monitoring across year. Test-retest reliability: Test-retest reliability is evaluated by administering a same test to same individuals twice within a short interval and correlating scores from the two test administrations. Test-retest reliability provides some measure of reliability without the confound of the (expected) student growth between administration. It also ensures representativeness and stability of a test over time

*Describe the sample(s), including size and characteristics, for each reliability analysis conducted.

Study a: 1- week test-retest reliability: The data were collected on a total of 633 students. Of the sample, about 51% female, 75% white, 14% Black, and 7% Hispanic, with 4% Asian or Native American. About 29% were eligible for free or reduced lunch; 20% Title 1 students; and 6% were in special education programs. There were 4 English as a second language/limited English proficiency (ESL/LEP) students, 10 gifted/talented students, and 1 disabled student. Study b: Alternate form reliability: Participants included 86 kindergarten students from a midsized city in Northwestern Massachusetts. Of the total sample, 93% were Caucasian, 2% African American, 2% Hispanic, and 2% Asian and consisted of 44 girls and 42 boys. Study c: Alternate form reliability: Participants were from kindergarten, first, second, and third grade classrooms in two elementary schools in separate school districts in Lane County, Oregon. The sample from School 1 consisted of 88% of white, non-Hispanic, 7% of Hispanic, 3% of Asian/Pacific Islander, 1% of Black, non-Hispanic, and 1% of Native American. Of the School 1 sample, 41% were eligible for free and reduced lunch. The sample from School 2 consisted of 94% of white, non-Hispanic, 4% of Hispanic, 1% of Asian/Pacific Islander, 1% of Black, non-Hispanic, and less than 1% of Native American. Of the School 2 sample, 42% were eligible for free and reduced lunch.

*Describe the analysis procedures for each reported type of reliability.

Test-retest reliability: Students were re-administered the same test in the three weeks following the end-of-year benchmark assessment. Test-retest reliability was estimated as the correlation coefficient between the test and retest. Alternate form reliability: Students were administered three different forms for the middle of year ORF test. Alternate-form reliability of a single form was estimated by the correlation between the score recorded on the other forms. The median of correlation coefficients between three forms is reported. Delayed alternate form reliability was estimated by correlating ORF scores measured at different measurement points across year—beginning-, middle-, and end of year. The median of correlation coefficients between the three benchmark assessments is reported. Internal consistency: The reliability of the ORF fall to spring gain score, a confirmatory factor analysis (CFA) measurement model that included the three fall ORF passage scores to define latent fall ORF ability and the three spring ORF passages to define latent spring ORF ability to estimate the reliability was used. The covariance between the two fall median scores is an estimate of the fall true score variance, the covariance between the two spring median scores is an estimate of the spring true score variance and the four covariances between the two fall median scores and two spring median scores are each an estimate of the covariance between fall and spring true scores. The average of the four covariances as the best single estimate of the fall-spring true score covariance. The true gain score variance was computed as fall true score variance plus spring true score variance minus two times the covariance of fall and spring true scores. For the observed gain score variance, the observed fall and spring variances in the same formula in place of the true score variances were used. Reliability coefficient was computed as the ratio of the true gain score variance to the observed gain score variance.

*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:

(a) McBride, J. R., Ysseldyke, J., Milone, M. & Stickney, E. (2010). Technical adequacy and cost benefit of four measures of early literacy. Canadian Journal of School Psychology, 25, 189-204. DOI: 10.1177/0829573510363796 (b) Hintze, J. M., Ryan, A. L., & Stoner, G. (2003). Concurrent validity and diagnostic accuracy of the Dynamic Indicators of Basic Early Literacy Skills and the Comprehensive Test of Phonological Processing. School Psychology Review, 32, 541-556. Reliability Type Grade n Coefficient 95% CI: Lower 95% CI: Upper 1-month alternate form (c) Kindergarten 71-215 0.89 0.82-0.86* 0.91-0.93* 1-month alternate form (c) First Grade 80-231 0.86 0.79-0.82* 0.89-0.91* (c) Good, R.H., Kaminski, R.A., Shinn, M., Bratten, J., Shinn, M., Laimon, D., Smith, S., & Flindt, N. (2004). Technical Adequacy of DIBELS: Results of the Early Childhood Research Institute on measuring growth and development (Technical Report, No. 7). Eugene, OR: University of Oregon. * Indicates the ranges of confidence interval depending on the sample size

Manual cites other published reliability studies:

Provide citations for additional published studies.

Kaminski, R. A., & Good, R. H., III. (1996). Toward a technology for assessing basic early literacy skills. School Psychology Review, 25(2), 215-227

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
Rating

*Describe each criterion measure used and explain why each measure is appropriate, given the type and purpose of the tool.

easyCBM Letter Sounds is a individually administered screening measure to be used for establishing benchmarks and monitoring progress. It takes 1 minute to administer. The median of alternate form reliability is .85, and the median of test-retest reliability is .66. The measure’s predictive validity with SAT-10 is .68, and the concurrent validity with SAT-10 is .72. TOWRE sight word efficiency (SWE) is a measure of accuracy and fluency in reading phonetically regular and irregular words from the TOWRE (Torgesen et al., 1999). The number of words spoken correctly within 45 seconds is counted, and this constitutes the final score for sight word efficiency. This subtest’s concurrent validity with the WRMT-R Word Identification subtest is .92. Alternate form reliability for the Sight Word Efficiency subtest is .97 and test-retest reliability is .96 (Torgesen et al., 1999). Stanford Achievement Test-10 (SAT-10) Reading Comprehension is a published norm-referenced test designed to assess reading comprehension. Students are required to read text passages and then answer questions. Note that because letter naming is a very specific and rapidly developing skill, validity correlations with a general outcome measure, such as the SAT-10, at the end of the year are expected to be somewhat weaker than for skills that develop more evenly over time. However, they are still expected to be strong relative to Cohen’s rule of thumb for interpreting correlations (i.e., over .50).

*Describe the sample(s), including size and characteristics, for each validity analysis conducted.

Kindergarten concurrent validity: The sample included 1,511 kindergarteners from a school district in a northwest state. Of the sample, 48% were males, 50% white, 21% American Indian/Alaskan Native, 7% Asian, 2% African American, and 2% Hawaiian/Pacific Islanders. The sample had 35% of Hispanic ethnicity. 27% of the students in the sample had LEP status, and 8% of the students were eligible for special education. Kindergarten predictive validity: The sample included 218 kindergarteners from a large, rural primary school in northern Georgia. The demographic data were available for 159, of whom 66% were boys, 62% Caucasian, 30% African American, 2% Hispanic, 1% Asian, and 6% mixed ethnicities. 43% of the participants for whom demographic data were eligible for free or reduced lunch. Grade 1 concurrent validity: The sample included 1,592 first grade students from a school district in a northwest state. Of the sample, 50% were males, 51% white, 22% American Indian/Alaskan Native, 7% Asian, 2% African American, and 1% Hawaiian/Pacific Islanders. The sample had 33% of Hispanic ethnicity. 24% of the students in the sample had LEP status, and 9% of the students were eligible for special education. Grade 1 predictive validity: The sample in the study consisted of 27,813 first grade students from 321 schools in Florida. Only students with complete data on both outcome measures (ORF and SAT-10) were included in the study. The graph below shows the sample demographics

*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:

Reliability Type Grade Criterion n Coefficient 95% CI: Lower 95% CI: Upper Predictive Kindergarten Spring G1 CBM-R 50-59 0.72 0.55-0.57* 0.82-0.83* (a) Center on Teaching and Learning (2017). Unpublished data [HSD Project]. Eugene, OR: University of Oregon. (b) Good, R.H., Kaminski, R.A., Shinn, M., Bratten, J., Shinn, M., Laimon, D., Smith, S., & Flindt, N. (2004). Technical Adequacy of DIBELS: Results of the Early Childhood Research Institute on measuring growth and development (Technical Report, No. 7). Eugene, OR: University of Oregon. (c) Rouse, H. R., & Fantuzzo, J. W. (2006). Validity of the Dynamic Indicators for Basic Early Literacy Skills as an indicator of early literacy for urban kindergarten children. School Psychology Review, 35, 341-355. (d) Burke, M. D., Hagan-Burke, S., Kwok, O., & Parker, R. (2009). Predictive validity of early literacy indicators from the middle of kindergarten to second grade. The Journal of Special Education, 42, 209-226. (e) Powell-Smith, K. A. & Cummings, K. (2007). What’s PSF got to do with it?. Retrieved from https://dibels.org/papers/PSF_PCRC_013107.pdf * Indicates the ranges of confidence interval depending on the sample size

Manual cites other published reliability studies:

Yes

Provide citations for additional published studies.

Cummings, K. D., Kaminski, R. A., Good, R. H. & O’Neil, M. (2011). Assessing phonemic awareness in preschool and kindergarten: Development and initial validation of First Sound Fluency. Assessment for Effective Intervention, 36(2) 94–106 Goffreda, C. T., DiPerna, J. C., & Pedersen, J. A. (2009). Preventive screening for early readers: Predictive validity of the Dynamic Indicators of Basic Early Literacy Skills (DIBELS). Psychology in the Schools, 46(6), 539-552. Kaminski, R. A., & Good, R. H., III. (1996). Toward a technology for assessing basic early literacy skills. School Psychology Review, 25(2), 215-227. Munger, K. A. & Blachman, B. A. (2013). Taking a "simple view" of the Dynamic Indicators of Basic Early Literacy Skills as a predictor of multiple measures of third-grade reading comprehension, Psychology in the Schools, 50(7), 722-737.

Describe the degree to which the provided data support the validity of the tool.

Overall, the validity of DIBELS 6th LNF measure is well supported by criterion measures. From kindergarten to first grade, DIBELS 6th LNF measure scores are moderately to strongly correlated with the easyCBM Letter Sounds, TOWRE–SWE, SAT-10 Total Reading, First Grade DRA Instructional Reading Level, and First Grade CBM–R, with validity coefficients ranging from r = .55 – .78.

Do you have validity data that are disaggregated by gender, race/ethnicity, or other subgroups (e.g., English language learners, students with disabilities)?

No

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:

No

Provide citations for additional published studies.

Bias Analysis

Grade	Kindergarten	Grade 1
Rating	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.