Table 2.
GLS model results for performance and sampling duration
| Factors | Levels | E1 | E2 | E3 | E4 | |
|---|---|---|---|---|---|---|
| Performance | Intercept | 0.93 (0.02)*** | 0.95 (0.06)*** | 0.90 (0.07)*** | 0.77 (0.11)*** | |
| Taska,b | GNG | Reference | Reference | Reference | Reference | |
| TAC | −0.09 (0.02)*** | −0.12 (0.03)*** | 0.02 (0.02) | −0.004 (0.06) | ||
| Odor seta,b | Train | Reference | Reference | Reference | Reference | |
| Extreme | −0.32 (0.03)*** | −0.25 (0.06)*** | — | — | ||
| S2 | −0.20 (0.03)*** | −0.18 (0.07)** | −0.02 (0.09) | −0.08 (0.14) | ||
| S3 | −0.18 (0.03)*** | −0.21 (0.07)** | −0.06 (0.09) | — | ||
| S4 | −0.14 (0.03)*** | −0.19 (0.07)** | −0.14 (0.08) | 0.003 (0.14) | ||
| S5 | — | −0.10 (0.07) | — | — | ||
| S6 | — | −0.08 (0.07) | — | — | ||
| S8 | — | — | −0.11 (0.09) | — | ||
| Sampling duration | Intercept | 573 (28)*** | 550 (52)*** | 650 (40)*** | 527 (149)*** | |
| Taska,c,d | GNG | Reference | Reference | Reference | Reference | |
| TAC | −103 (21)*** | −31 (30) | −135 (16)*** | −111 (22)*** | ||
| Odor seta | Train | Reference | Reference | Reference | Reference | |
| Extreme | 4 (35) | −8 (62) | — | — | ||
| S2 | −91 (35)** | −39 (62) | −18 (49) | 24 (209) | ||
| S3 | −65 (35) | −33 (62) | 18 (49) | — | ||
| S4 | −27 (35) | −26 (63) | 39 (49) | 23 (208) | ||
| S5 | — | −38(64) | — | — | ||
| S6 | — | −55 (66) | — | — | ||
| S8 | — | — | 7 (50) | — |
Statistical significance is based upon Wald F tests, which are indicated in superscripts next to each factor (e.g., Task, Odor set) with values (a, E1; b, E2; c, E3; d, E4) for Tables 2–5. Odor sets are identified in the coefficient level column by name or S + number (See Table 1 for odors). Significant coefficient based upon t value given as follows: *0.05, **0.01, ***0.001. All durations are rounded to the nearest millisecond. Values in parentheses are SEs. Blank cells indicate factors or odor sets that were not used in a given experiment. The intercept represents the expected value given the reference level for each factor. A significant intercept means that it is statistically different from zero. For example, the intercept in E1 performance represents expected performance for a GNG rat on the training odor set and is different from zero. Values for levels other than the reference are with respect to the factor reference. To get the expected value of any specific combination of levels, one simply adds the value for the chosen level (within a factor) to the intercept. So, for E1 we would expect that a rat engaged in a TAC task would perform 9% worse than a GNG rat, on average, across all odor sets; or, that in E1 a GNG rat would perform, on average, the extreme odor set 32% worse than the training odor set.