**Options for analyzing below detectable lab values**

**Simple options include:**

- If the % of below detectable (BD) is very high, analyze as a binary variable (detectable vs. undetectable)
- If %BD is moderate (<25%), create discrete categories (like tertiles, quartiles, or quintiles)
- If %BD is rare (<5%), and values are highly skewed, replace BD values with the LOD/2, where LOD = limit of detection
- If %BD is rare (<5%), and values are less skewed, replace BD values with the LOD/sqrt(2)

Options 3 and 4 can introduce bias and reduce power; if the %BD is extremely rare, this should have little effect on the results.

**More complex options:**

1. If the lab value is the outcome, use Tobit regression to handle BD values (note that lab value may first need to be normalized, depending on the software used):

In Stata: http://www.stata.com/help.cgi?tobit

In SAS: use proc lifereg or proc qlim: http://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_lifereg_sect035.htm

2. Use multiple imputation to replace BD values with imputed values. The missing at random assumption is violated, so a modified approach using a Gibbs sampler is needed: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3596170/

3. Use propensity score weighting (model probability of being BD, then incorporate the result in the model using detectable values).

http://www.ncbi.nlm.nih.gov/pubmed/15923407

**References**:

Baker SG, Fitzmaurice GM, Freedman LS, Kramer BS. Simple adjustments for randomized trials with nonrandomly missing or censored outcomes arising from informative covariates. Biostatistics. 2006;7(1):29–40. [PubMed]

Hughes MD. Analysis and design issues for studies using censored biomarker measurements with an example of viral load measurements in HIV clinical trials. Stat Med. 2000;19:3171–3191. [PubMed]

Lambert D, Peterson B, Terpenning I. Nondetects, detection limits, and the probability of detection. J Am Stat Assoc. 1991;86:266–277.

Lubin JH, Colt JS, Camann D, Davis S, Cerhan JR, Severson RK, et al. Epidemiologic evaluation of measurement data in the presence of detection limits. Environ Health Perspect. 2004;112:1691–1696. [PMC free article] [PubMed]