Sampling and Estimation

Nonresponse Adjusted Sample Size Calculator

Inflates a completed-sample target for an expected nonresponse percentage. The form displays ninvite = ceil(ntarget / (1-r)) beside invitations required, using a worked condition that can be recalculated with the labeled inputs.

Statistical inputs

Define the sample plan in this example

completes
%
Calculated result

Invitations required

Result
—
ninvite = ceil(ntarget / (1-r))

    Interpreting the requested invitations required

    The nonresponse adjusted sample size page inflates a completed-sample target for an expected nonresponse percentage.

    Invitations required is limited to the statistical quantity named by the result panel. The invitations required calculation does not silently add a population, time horizon, causal direction, or decision threshold that is absent from the fields.

    Before entering the nonresponse adjusted sample size data

    • Completed sample target: For invitations required, the worked value for completed sample target is 400 completes. Treat the completed sample target entry (400 completes) explicitly as a count, proportion, rate, estimate, or model parameter before comparing invitations required conditions. The form enforces minimum 1.
    • Expected nonresponse: For invitations required, the worked value for expected nonresponse is 20 %. Treat the expected nonresponse entry (20 %) explicitly as a count, proportion, rate, estimate, or model parameter before comparing invitations required conditions. The form enforces minimum 0, maximum 99.99.

    The entries used for invitations required must refer to one coherent analysis condition. Combining incompatible populations, periods, or measurement definitions can produce valid invitations required arithmetic for a nonexistent study.

    Working through the nonresponse adjusted sample size formula

    ninvite = ceil(ntarget / (1-r))

    For invitations required, match every symbol in the relationship to a labeled field before substituting numbers. Invitations required is reported in invitations.

    While checking invitations required, inspect every denominator in ninvite = ceil(ntarget / (1-r)). For invitations required, a zero or near-zero denominator can make invitations required undefined or unstable.

    A fixed case for comparison

    The default invitations required condition is Completed sample target = 400 completes, Expected nonresponse = 20 %.

    To obtain 400 completes with 20 percent nonresponse, invite at least 500 people.

    The live calculator reports Invitations required 500 invitations · Expected response rate 80 %. Repeating one intermediate step from ninvite = ceil(ntarget / (1-r)) provides a fixed invitations required reference check for later code changes.

    Limits on interpreting invitations required

    The calculation assumes the planning response rate is credible; it does not correct bias when respondents differ systematically from nonrespondents.

    For nonresponse adjusted sample size, a planning or survey quantity is only as defensible as its frame, response assumptions, clustering, and population definition.

    Reading invitations required in context

    When interpreting nonresponse adjusted sample size, changing a design effect, allocation rule, response rate, or finite-population boundary can matter more than another displayed decimal.

    As a second check for invitations required, reversing the numerator and denominator answers a different question, so retain the direction printed in ninvite = ceil(ntarget / (1-r)).

    Varying a single nonresponse adjusted sample size input at a time

    Change completed sample target while holding the remaining entries fixed, then state why the direction and size of the invitations required change are plausible from ninvite = ceil(ntarget / (1-r)).

    Repeat the invitations required exercise with expected nonresponse. If a modest defensible change materially alters the interpretation, report both conditions rather than presenting that invitations required scenario as exact.

    Where a plausible invitations required can go wrong

    Before accepting invitations required, compare every entered value with its label, unit, and allowed domain after reading the printed relationship from left to right.

    For invitations required, do not move a number between fields merely because the units look compatible; each label gives the number a different statistical role.

    Another invitations required failure occurs when a rounded output is reused as though it were the original measurement. Carry guard digits through calculations that depend on invitations required, then round only the reported value.

    A reproducible record of invitations required

    Report invitations required using ninvite = ceil(ntarget / (1-r)), followed by the entered values, units, exclusions, and analysis date. Name the invitations required population or dataset boundary instead of leaving it implicit.

    Keep the full calculator output with the record, including Invitations required 500 invitations · Expected response rate 80 %. A later invitations required review can then distinguish a changed input from a different convention or software implementation.

    Questions about invitations required

    Does invitations required establish a causal or population conclusion?

    No. The displayed nonresponse adjusted sample size value is conditional on the entered data and named method. The invitations required design, measurement process, and assumptions determine what can be concluded beyond those values.

    How should invitations required be rounded?

    Keep the unrounded invitations required for subsequent arithmetic, then report only the precision supported by the source measurements and the decision context. Extra digits in invitations required do not correct sampling or model error.

    Which input deserves the closest boundary check?

    For invitations required, start with expected nonresponse and then completed sample target. Confirm the invitations required units and allowed domain because a valid-looking entry can still describe the wrong statistical setup.