Choice experiments (CEs) are commonly used to estimate monetary values for characteristics of public goods, but there are unresolved design issues. The number of alternatives is one of them. Increasing the number of alternatives increases the potential information learned from a sample of a limited size, which may assist subjects in selecting a preferred alternative (referred as matching) or may make choices more difficult (referred as complexity). A convergent-validity study is conducted to compare CE designs with status quo (SQ) plus one, two or three alternatives. To enhance convergent-validity insights, we use the SQ plus one treatment, which is a theoretically supported treatment, as a counterfactual treatment. We fail to find convergent validity between the one-alternative treatment and the two- and three-alternative treatments. Yet there is little difference in welfare estimates between the two- and three-alternative treatments. We find a net matching effect in the one-alternative treatment as the number of attribute-level changes increases, which reduces the likelihood of choosing the SQ alternative. We find net complexity effects in the two- and three-alternative treatments, which increases the likelihood of subjects choosing the SQ alternative as the number of choice questions increases. Our results support the use of SQ plus one-alternative design, suggest caution when using a SQ plus two- and three-alternative designs.