Is it correct to concatenate (pseudo-)random byte values before testing them with the NIST suite or tools like dieharder? Let's assume I have thousands of (pseudo-)random 4-byte values. The values are 4 byte random values which a blackbox device gave me. I got these values by requesting them. In between others might have requested them too (I don't know about that). Now I'd like to test them for randomness. There are tools for this like dieharder or the NIST Statistical Test Suite.

Is it valid to just concatenate the thousands of 4-byte values so that I end up with one very long byte (n * 1000 * 4 byte) stream which I then feed into these tools? 

Is it correct that it doesn't matter for the tests how long the individual values (4-byte) were before? (Because the test tool wouldn't know that I had 4-byte values in the beginning, once I concatenated them?).

Edit:
The question is meant as a general question. The actual underlying problem is how to examine seed values for randomness, which I obtained via UDS Security Access (see https://en.wikipedia.org/wiki/Unified_Diagnostic_Services#Services $27).
Is it valid to just concatenate the thousands of 4-byte values so that I end up with one very long byte (n * 1000 * 4 byte) stream which I then feed into these tools?
Is it correct that it doesn't matter for the tests how long the individual values (4-byte) were before?

Yes for both. The fact that others may have obtained (and removed) randomness from the source while it was sampled, or/and that the samples are grouped in some particular way for testing, does not prevent from testing what's obtained. And that can not cause a valid test to fail more often, assuming the source's full output is indistinguishable from random (including for said others trying to make the test pass, or fail).
On the other hand, those same facts could make the test become arbitrarily less capable of detecting some faults. As an extreme example, a source that always repeat each byte that it outputs might become indistinguishable from true random if we sub-sample its output, keeping every odd byte.

The actual underlying problem is how to examine seed values for randomness.

Dieharder or the NIST Statistical Test Suite alone can't give any assurance of that. At best, they can indicate a fail with high confidence, which saves from performing further work (beyond checking that the test was correctly performed/works). If they indicate pass, no other firm conclusion can be reached on that basis alone. It is needed to know how the seed values are generated, and that can't be determined by a test of the seed values.

As a proof that these tests can not validate the fitness for cryptographic purposes of a source of unknown build, consider a RNG with:

a real-time clock keeping UTC time in second, initializing 128-bit register at startup after a delay of 1 second
with the register then repeatedly encrypted using AES-256 and a key to produce the next register value, which concatenated 128-bit values form the bulk of the output, queried over a gigabit Ethernet interface.

This source will pass any black-box testing that does not reject a good generator, including tests scrutinizing power-on, as long as the test does not use AES-256 and the correct key.
But this source is disastrous from a cryptographic perspective. Given the key and when the black box was started, its output is predictable. Given the key and a fragment of a sequence, all the rest can be computed. Some party eating bytes from the source in the background can even decide what another party using the source will get!

As pointed by others, many statistical tests, including some of the DieHarder suite, require megabytes of input. The full Dieharder needs gigabytes.
However, in the context of a cryptographic RNG of proper structure, these tests requiring a lot of input are not needed. The tests that make sense are those on the unconditioned (or lightly conditioned) entropy source, used to seed a CSPRNG. The source is validated by tests which purpose is to ensure that it delivers some entropy. The CSPRNG is validated by examination of its design, and Known Answer Tests. Some monitoring in the RNG should detect a fault in the source and in this case prevent output. The combination might be checked by an extra test of the whole thing, but that's meaningful only if there is some assurance, obtained otherwise, that the overall structure really is the source seeding the CSPRNG, and being monitored.